Couchbase Connection
This documentation is based on version 21.0.8257 of the connector.
This documentation is based on version 21.0.8257 of the connector.
The Jitterbit Connector for Couchbase models Couchbase documents in a bucket as tables in a relational database; connect to Couchbase Server versions 4.0 and up, Enterprise Edition or Community Edition.
To connect to data, set the Server property to the hostname or IP address of the Couchbase server(s) you are authenticating to. If your Couchbase server is configured to use SSL, you can enable it either by using an https URL for Server (like 'https://couchbase.server'), or by setting the UseSSL property to True.
By default, the connector connects to the N1QL Query service. In order to connect to the Couchbase Analytics service, you will also need to set the CouchbaseService property to Analytics.
A few special settings are required to connect to Couchbase Cloud:
The connector supports several forms of authentication depending upon how your Couchbase Server is configured. Couchbase Cloud only accepts Standard Authentication, while Couchbase Server accepts all forms.
To authenticate with standard authentication, set the following:
The connector supports authenticating with client certificates when SSL is enabled. To use client certificate authentication, set the following properties.
You can also authenticate using using a credentials file containing multiple logins. This is included for legacy use and is not recommended when connecting to a Couchbase Server that supports role-based authentication.
Couchbase is a schema-free document database that provides high performance, availability, and scalability. These features are not necessarily incompatible with a standards-compliant query language like SQL-92.
The connector models the schema-free Couchbase objects into relational tables and translates SQL queries into N1QL or SQL++ (Analytics) queries to get the requested data. In this section we will show various schemes that the connector offers to bridge the gap with relational SQL and a document database.
When the connector first connects to Couchbase, it opens each bucket and scans a configurable number of rows from that bucket. It uses those rows to determine the columns in that bucket and their data types, as well as how to build flavored and child tables for any arrays within those documents. For Couchbase Enterprise version 4.5.1 and later, the connector may can also be configured to use the INFER command when TypeDetectionScheme is set to INFER. This allows the connector to get a more accurate column listing for the bucket, and to detect more complex flavors.
When using the Analytics service, the connector only does column and child table detection. Flavored tables are provided by Couchbase itself using shadow datasets. Also, Analytics mode does not currently have INFER support, so only row scan is supported.
For more details, refer to Automatic Schema Discovery to see how flavored tables and child tables are modelled from Couchbase data. Setting NumericStrings is also recommended as it can avoid type detection issues with certain kinds of text data.
Optionally, you can use Custom Schema Definitions to project your chosen relational structure on top of a Couchbase object. This allows you to define your chosen column names, their data types, and the locations of their values in the Couchbase document.
See Query Mapping for more details on how various N1QL and SQL++ operations are represented as SQL.
See Vertical Flattening for more details on how arrays and objects are mapped into fields.
See JSON Functions for more details on how to extract data from raw JSON strings.
If the documents within a bucket contain fields with arrays, then the connector will expose those fields as their own tables in addition to exposing them as JSON aggregates on the main table. The structure of these child tables depends upon whether the array contains objects or primitive values.
If the arrays contain primitive values like numbers or strings, the child table will have only two columns: one called "Document.Id" which is the primary key of the document containing the array, and one called "value" which contains the value within the array. For example, if the bucket "Games" contains these documents:
/* Primary key "1" */
{
"scores": [1,2,3]
}
/* Primary key "2" */
{
"scores": [4,5,6]
}
The connector will build a table called "Games_scores" containing these rows:
| Document.Id | value |
| 1 | 1 |
| 1 | 2 |
| 1 | 3 |
| 2 | 4 |
| 2 | 5 |
| 2 | 6 |
If the arrays contain objects, the child table will have a column for each field that occurs within the objects, as well as a "Document.Id" column which contains the primary key of the document containing the array. For example, if the bucket "Games" contains these documents:
/* Primary key "1" */
{
"moves": [
{"piece": "pawn", "square": "c3"},
{"piece": "rook", "square": "d5"}
]
}
/* Primary key "2" */
{
"moves": [
{"piece": "knight", "square": "f1"},
{"piece": "bishop", "square": "e4"}
]
}
The connector will build a table called "Games_moves" containing these rows:
| Document.Id | piece | square |
| 1 | pawn | c3 |
| 1 | rook | d5 |
| 2 | knight | f1 |
| 2 | biship | e4 |
Note that the above data model is not fully relational, which has important limitations for use-cases that involve complex JOINs or DML operations on child tables. The NewChildJoinsMode connection property exposes an alternative data model which avoids these limitations. Please refer to its page in the connection property section of the documentation for more details.
The connector can also detect when there are multiple types of documents within the same bucket, as long as TypeDetectionScheme is set to Infer or DocType and CouchbaseService is set to N1QL. These different types of documents are exposed as their own tables containing only the appropriate rows.
For example, the bucket "Games" contains documents which have a "type" value of either "chess" or "football":
/* Primary key "1" */
{
"type": "chess",
"result": "stalemate"
}
/* Primary key "2" */
{
"type": "chess",
"result": "black win"
}
/* Primary key "3" */
{
"type": "football",
"score": 23
}
/* Primary key "4" */
{
"type": "football",
"score": 18
}
The connector will create three tables for this bucket: one called "Games" which contains all the documents:
| Document.Id | result | score | type |
| 1 | stalemate | NULL | chess |
| 2 | black win | NULL | chess |
| 3 | NULL | 23 | football |
| 4 | NULL | 18 | football |
One called "Games.chess" which contains only documents where the type is "chess":
| Document.Id | result | type |
| 1 | stalemate | chess |
| 2 | black win | chess |
And one called "Games.football" which contains only documents where the type is "football":
| Document.Id | score | type |
| 3 | 23 | football |
| 4 | 18 | football |
Note that the connector will not include columns in a flavored table that are not defined on the documents in that flavor. For example, even though both the "result" and "score" columns are included on the base table, "Games.chess" only includes "result" and "Games.football" only includes "score".
/* Primary key "1" */
{
"type": "chess",
"results": ["stalemate", "white win"]
}
/* Primary key "2" */
{
"type": "chess",
"results": ["black win", "stalemate"]
}
/* Primary key "3" */
{
"type": "football",
"scores": [23, 12]
}
/* Primary key "4" */
{
"type": "football",
"scores": [18, 36]
}
Then the connector will generate these tables:
| Table Name | Child Field | Flavor Condition |
| Games | ||
| Games_results | results | |
| Games_scores | scores | |
| Games.chess | "type" = "chess" | |
| Games.chess_results | results | "type" = "chess" |
| Games.football | "type" = "football" | |
| Games.football_scores | scores | "type" = "football" |
The connector maps SQL-92-compliant queries into corresponding N1QL or SQL++ queries. Although the mapping below is not complete, it should help you get a sense for the common patterns the connector uses during this transformation.
The SELECT statements are translated to the appropriate N1QL SELECT query as shown below. Due to the similarities between SQL-92 and N1QL, many queries will simply be direct translations.
One major difference is that when the schema for a given Couchbase bucket exists in the connector, a SELECT * query will be translated to directly select the individual fields in the bucket. The connector will also automatically create a Document.Id column based on the primary key of each document in the bucket.
| SQL Query | N1QL Query |
| SELECT * FROM users | SELECT META(`users`).id AS `id`, ... FROM `users` |
| SELECT [Document.Id], status FROM users | SELECT META(`users`).id AS `Document.Id`, `users`.`status` FROM `users` |
| SELECT * FROM users WHERE status = 'A' OR age = 50 | SELECT META(`users`).id AS `id`, ... FROM `users` WHERE TOSTRING(`users`.`status`) = "A" OR TONUMBER(`users`.`age`) = 50 |
| SELECT * FROM users WHERE name LIKE 'A%' | SELECT META(`users`).id AS `id`, ... FROM `users` WHERE TOSTRING(`users`.`name`) LIKE "A%" |
| SELECT * FROM users WHERE status = 'A' ORDER BY [Document.Id] DESC | SELECT META(`users`).id AS `id`, ... FROM `users` WHERE TOSTRING(`users`.`status`) = "A" ORDER BY META(`users`).id DESC |
| SELECT * FROM users WHERE status IN ('A', 'B') | SELECT META(`users`).id, ... FROM `users` WHERE TOSTRING(`users`.`status`) IN ["A", "B"] |
Note that conditions can include extra type functions if the connector detects that a type conversion may be necessary. You can disable these type conversions using the StrictComparison property. For clarity, the rest of the N1QL samples are shown without these extra conversion functions.
When a query has either equals or IN clause that targets the Document.Id column, and there is no OR clause to override it, the connector will convert the Document.Id filter into a USE KEYS clause. This avoids the overhead of scanning an index because the document keys are already known to the N1QL engine (this optimization does not apply to the Analytics CouchbaseService).
| SQL Query | N1QL Query |
| SELECT * FROM users WHERE [Document.Id] = '1' | SELECT ... FROM `users` USE KEYS ["1"] |
| SELECT * FROM users WHERE [Document.Id] IN ('2', '3') | SELECT ... FROM `users` USE KEYS ["2", "3"] |
| SELECT * FROM users WHERE [Document.Id] = '4' OR [Document.Id] = '5' | SELECT ... FROM `users` USE KEYS ["4", "5"] |
| SELECT * FROM users WHERE [Document.Id] = '6' AND status = 'A' | SELECT ... FROM `users` USE KEYS ["6"] WHERE `status` = "A" |
In addition to being used for SELECT queries, the same optimization is performed for DML operations as shown below.
As long as all the child tables in a query share the same parent, and they are combined using INNER JOINs on their Document.Id columns, the connector will combine the JOINs into a single UNNEST expression. Unlike N1QL UNNEST queries, you must explicitly JOIN with the base table if you want to access its fields.
| SQL Query | N1QL Query |
| SELECT * FROM users_posts | SELECT META(`users`).id, `users_posts`.`text`, ... FROM `users` UNNEST `users`.`posts` AS `users_posts` |
| SELECT * FROM users INNER JOIN users_posts ON users.[Document.Id] = users_posts.[Document.Id] | SELECT META(`users`).id, `users`.`name`, ..., `users_posts`.`text`, ... FROM `users` UNNEST `users`.`posts` AS `users_posts` |
| SELECT * FROM users INNER JOIN users_posts ... INNER JOIN users_comments ON ... | SELECT ... FROM `users` UNNEST `users`.`posts` AS `users_posts` UNNEST `users`.`comments` AS `users_comments` |
Flavored tables always have the appropriate condition included when you query, so that only documents from the flavor will be returned:
| SQL Query | N1QL Query |
| SELECT * FROM [users.subscriber] | SELECT ... FROM `users` WHERE `docType` = "subscriber" |
| SELECT * FROM [users.subscriber] WHERE age > 50 | SELECT ... FROM `users` WHERE `docType` = "subscriber" AND `age` > 50 |
N1QL has several built-in aggregate functions. The connector makes extensive use of this for various aggregate queries. See some examples below:
| SQL Query | N1QL Query |
| SELECT Count(*) As Count FROM Orders | SELECT Count(*) AS `count` FROM `Orders` |
| SELECT Sum(price) As total FROM Orders | SELECT Sum(`price`) As `total` FROM `Orders` |
| SELECT cust_id, Sum(price) As total FROM Orders GROUP BY cust_id ORDER BY total | SELECT `cust_id`, Sum(`price`) As `total` FROM `Orders` GROUP BY `cust_id` ORDER BY `total` |
| SELECT cust_id, ord_date, Sum(price) As total FROM Orders GROUP BY cust_id, ord_date Having total > 250 | SELECT `cust_id`, `ord_date`, Sum(`price`) As `total` FROM `Orders` GROUP BY `cust_id`, `ord_date` Having `total` > 250 |
The SQL INSERT statement is mapped to the N1QL INSERT statement as shown below. This works the same for both top-level fields as well as fields produced by Vertical Flattening:
| SQL Query | N1QL Query |
| INSERT INTO users([Document.Id], age, status) VALUES ('bcd001', 45, 'A') | INSERT INTO `users`(KEY, VALUE) VALUES ('bcd001', { "age" : 45, "status" : "A" }) |
| INSERT INTO users([Document.Id], [metrics.posts]) VALUES ('bcd002', 0) | INSERT INTO `users`(KEY, VALUE) VALUES ('bcd002', {"metrics': {"posts": 0}}) |
Inserts on child tables are converted internally into N1QL UPDATEs using array operations. Since that this does not create the top-level document, the Document.Id provided must refer to a document that already exists.
Another limitation of child table inserts is that multi-valued inserts must all use the same Document.Id. The provider will verify this before modifying any data and raise an error if this constraint is violated.
| SQL Query | N1QL Query |
| INSERT INTO users_ratings([Document.Id], value) VALUES ('bcd001', 4.8), ('bcd001', 3.2) | UPDATE `users` USE KEYS "bcd001" SET `ratings` = ARRAY_PUT(`ratings`, 4.8, 3.2) |
| INSERT INTO users_reviews([Document.Id], score) VALUES ('bcd002', 'Great'), ('bcd002', 'Lacking') | UPDATE `users` USE KEYS "bcd001" SET `ratings` = ARRAY_PUT(`ratings`, {"score": "Great"}, {"score": "Lacking"}) |
Bulk inserts are also supported the SQL Bulk Insert is converted as shown below:
INSERT INTO users#Temp([Document.Id], KEY, VALUE) VALUES('bcd001', 45, "A")
INSERT INTO users#Temp([Document.Id], KEY, VALUE) VALUES('bcd002', 24, "B")
INSERT INTO users SELECT * FROM users#Temp
is converted to:
INSERT INTO `users` (KEY, VALUE) VALUES
('bcd001', {"age": 45, "status": "A"}),
('bcd002', {"age": 24, "status": "B"})
Like multi-valued inserts on child tables, all the rows in a bulk insert must also have the same Document.Id.
The SQL UPDATE statement is mapped to the N1SQL UPDATE statement as shown below:
| SQL Query | N1QL Query |
| UPDATE users SET status = 'C' WHERE [Document.Id] = 'bcd001' | UPDATE `users` USE KEYS ["bcd001"] SET `status` = "C" |
| UPDATE users SET status = 'C' WHERE age > 45 | UPDATE `users` SET `status` = "C" WHERE `age` > 45 |
When updating a child table, the SQL query is converted to an UPDATE query using either a "FOR" expression or an "ARRAY" expression:
| SQL Query | N1QL Query |
| UPDATE users_ratings SET value = 5.0 WHERE value > 5.0 | UPDATE `users` SET `ratings` = ARRAY CASE WHEN `value` > 5.0 THEN 5 ELSE `value` END FOR `value` IN `ratings` END |
| UPDATE users_reviews SET score = 'Unknown' WHERE score = '' | UPDATE `users` SET `$child`.`score` = 'Unknown' FOR `$child` IN `reviews` WHEN `$child`.`score` = "" END |
| SQL Query | N1QL Query |
| UPDATE [users.subscriber] SET status = 'C' WHERE age > 45 | UPDATE `users` SET `status` = "C" WHERE `docType` = "subscriber" AND `age` > 45 |
The SQL DELETE statement is mapped to the N1QL DELETE statement as shown below:
| SQL Query | N1QL Query |
| DELETE FROM users WHERE [Document.Id] = 'bcd001' | DELETE FROM `users` USE KEYS ["bcd001"] |
| DELETE FROM users WHERE status = 'inactive' | DELETE FROM `users` WHERE `status` = "inactive" |
When deleting from a child table, the SQL query is converted to an UPDATE query using an "ARRAY" expression:
| SQL Query | N1QL Query |
| DELETE FROM users_ratings WHERE value < 0 | UPDATE `users` SET `ratings` = ARRAY `value` FOR `value` IN `ratings` WHEN NOT (`value` < 0) END |
| DELETE FROM users_reviews WHERE score = '' | UPDATE `users` SET `reviews` = ARRAY `$child` FOR `$child` IN `reviews` WHEN NOT (`$child`.`score` = "") END |
| SQL Query | N1QL Query |
| DELETE FROM [users.subscriber] WHERE status = 'inactive' | DELETE FROM `users` WHERE `docType` = "subscriber" AND status = "inactive" |
/* Primary key "1" */
{
"address" : {
"building" : "1007",
"coord" : [-73.856077, 40.848447],
"street" : "Morris Park Ave",
"zipcode" : "10462"
},
"borough" : "Bronx",
"cuisine" : "Bakery",
"grades" : [{
"date" : "2014-03-03T00:00:00Z",
"grade" : "A",
"score" : 2
}, {
"date" : "2013-09-11T00:00:00Z",
"grade" : "A",
"score" : 6
}, {
"date" : "2013-01-24T00:00:00Z",
"grade" : "A",
"score" : 10
}, {
"date" : "2011-11-23T00:00:00Z",
"grade" : "A",
"score" : 9
}, {
"date" : "2011-03-10T00:00:00Z",
"grade" : "B",
"score" : 14
}],
"name" : "Morris Park Bake Shop",
"restaurant_id" : "30075445"
}
SELECT [address.building], [address.street] FROM restaurantsWould return this resultset:
| address.building | addres.street |
| 1007 | Morris Park Ave |
SELECT [address.coord.0], [address.coord.1] FROM restaurantsWould return this resultset:
| address.coord.0 | address.coord.1 |
| -73.856077 | 40.838447 |
Note that array flattening should only be used in cases where you know the number of array items in advance, such as with "address.coord" which will always contain two items. For arrays like "grades" which can contain arbitrary numbers of items, consider using the child tables described in Automatic Schema Discovery instead, since they will allow you to read all of the values within the array.
User-defined functions are a new feature provided by Couchbase 7 and up. They can be used with the connector like normal functions but with a special naming convention for using scoped functions. Normally the connector requires that functions already exist before they are used, to define them refer to the Couchbase documentation on CREATE FUNCTION queries. These may be run at the Couchbase console or with the connector in QueryPassthrough mode.
Couchbase has support for both scalar functions as well as functions that return results from subqueries. The connector supports scalar functions within its SQL dialect but subquery functions can only be used when QueryPassthrough is enabled. The rest of this section covers the connector's SQL dialect and assums that QueryPassthrough is disabled.
In both N1QL and Analytics mode, global user-defined functions can be accessed using either their simple names or their qualified names. The simple name is just the name of the function:
SELECT ageInYears(birthdate) FROM users
Global functions may also be invoked by qualifying them with the default namespace. Qualified names are quoted names that contain internal separators, which by default is a period though this can be changed using the DataverseSeparator property. In both N1QL and Analytics the global namespace is called Default:
SELECT [Default.ageInYears](birthdate) FROM users
Calling global functions using simple names is recommended. While the default qualfier is supported, its only intended use is for when a UDF clashes with a standard SQL function that the connector would otherwise translate.
Both N1QL and Analytics also allow functions to be defined outside of a global context. In Analytics functions can be attached to both dataverses and scopes which are called using two-part and three-part names respectively. In N1QL functions may only be attached to scopes so only three-part names may be used.
/* N1QL AND Analytics */ SELECT [socialNetwork.accounts.ageInYears](birthdate) FROM [socialNetwork.accounts.users] /* Analytics only */ SELECT [socailNetwork.ageInYears](birthdate) FROM [socialNetwork.accounts.users]
The connector can return JSON structures as column values. The connector enables you to use standard SQL functions to work with these JSON structures. The examples in this section use the following array:
[
{ "grade": "A", "score": 2 },
{ "grade": "A", "score": 6 },
{ "grade": "A", "score": 10 },
{ "grade": "A", "score": 9 },
{ "grade": "B", "score": 14 }
]
SELECT Name, JSON_EXTRACT(grades,'[0].grade') AS Grade, JSON_EXTRACT(grades,'[0].score') AS Score FROM Students;
| Column Name | Example Value |
| Grade | A |
| Score | 2 |
SELECT Name, JSON_COUNT(grades,'[x]') AS NumberOfGrades FROM Students;
| Column Name | Example Value |
| NumberOfGrades | 5 |
SELECT Name, JSON_SUM(score,'[x].score') AS TotalScore FROM Students;
| Column Name | Example Value |
| TotalScore | 41 |
SELECT Name, JSON_MIN(score,'[x].score') AS LowestScore FROM Students;
| Column Name | Example Value |
| LowestScore | 2 |
SELECT Name, JSON_MAX(score,'[x].score') AS HighestScore FROM Students;
| Column Name | Example Value |
| HighestScore | 14 |
SELECT [Document.Id], grade, score, DOCUMENT(*) FROM gradesFor example, that query would return:
| Document.Id | grade | score | DOCUMENT |
| 1 | A | 6 | {"document.id":1, "grade":"A", "score":6} |
| 2 | A | 10 | {"document.id":1, "grade":"A", "score":10} |
| 3 | A | 9 | {"document.id":1, "grade":"A", "score":9} |
| 4 | B | 14 | {"document.id":1, "grade":"B", "score":14} |
SELECT DOCUMENT(*) FROM gradesThis query would return:
| DOCUMENT | |
| {"grades":{"grade":"A", "score":6"}} | |
| {"grades":{"grade":"A", "score":10"}} | |
| {"grades":{"grade":"A", "score":9"}} | |
| {"grades":{"grade":"B", "score":14"}} |
In addition to Automatic Schema Discovery the connector also allows you to statically define the schema for your Couchbase object. Schemas are defined in text-based configuration files, which makes them easy to extend. You can call the CreateSchema stored procedure* to generate a schema file; see Automatic Schema Discovery for more information.
Set the Location property to the file directory that will contain the schema file. The following sections show how to extend the resulting schema or write your own.Let's consider the document below and extract out the nested properties as their own columns:
/* Primary key "1" */
{
"id": 12,
"name": "Lohia Manufacturers Inc.",
"homeaddress": {"street": "Main "Street", "city": "Chapel Hill", "state": "NC"},
"workaddress": {"street": "10th "Street", "city": "Chapel Hill", "state": "NC"}
"offices": ["Chapel Hill", "London", "New York"]
"annual_revenue": 35600000
}
/* Primary key "2" */
{
"id": 15,
"name": "Piago Industries",
"homeaddress": {street": "Main Street", "city": "San Francisco", "state": "CA"},
"workaddress": {street": "10th Street", "city": "San Francisco", "state": "CA"}
"offices": ["Durham", "San Francisco"]
"annual_revenue": 42600000
}
<rsb:info title="Customers" description="Customers" other:dataverse="" other:bucket=customers"" other:flavorexpr="" other:flavorvalue="" other:isarray="false" other:pathspec="" other:childpath="">
<attr name="document.id" xs:type="string" key="true" other:iskey="true" other:pathspec="" />
<attr name="annual_revenue" xs:type="integer" other:iskey="false" other:pathspec="" other:field="annual_revenue" />
<attr name="homeaddress.city" xs:type="string" other:iskey="false" other:pathspec="{" other:field="homeaddress.city" />
<attr name="homeaddress.state" xs:type="string" other:iskey="false" other:pathspec="{" other:field="homeaddress.state" />
<attr name="homeaddress.street" xs:type="string" other:iskey="false" other:pathspec="{" other:field="homeaddress.street" />
<attr name="name" xs:type="string" other:iskey="false" other:pathspec="" other:field="name" />
<attr name="id" xs:type="integer" other:iskey="false" other:pathspec="" other:field="id" />
<attr name="offices" xs:type="string" other:iskey="false" other:pathspec="" other:field="offices" />
<attr name="offices.0" xs:type="string" other:iskey="false" other:pathspec="[" other:field="offices.0" />
<attr name="offices.1" xs:type="string" other:iskey="false" other:pathspec="[" other:field="offices.1" />
<attr name="workaddress.city" xs:type="string" other:iskey="false" other:pathspec="{" other:field="workaddress.city" />
<attr name="workaddress.state" xs:type="string" other:iskey="false" other:pathspec="{" other:field="workaddress.state" />
<attr name="workaddress.street" xs:type="string" other:iskey="false" other:pathspec="{" other:field="workaddress.street" />
</rsb:info>
In Custom Schema Example, you will find the complete schema that contains the example above.
| Property | Meaning |
| other:dataverse | The name of the dataverse the dataset belongs to. Empty if not an Analytics view. |
| other:bucket | The name of the bucket or dataset within Couchbase |
| other:flavorexpr | The URL encoded condition in a flavored table. For example, "%60docType%60%20%3D%20%22chess%22". |
| other:flavorvalue | The name of the flavor in a flavored table. For example, "chess". |
| other:isarray | Whether the table is an array child table. |
| other:pathspec | This is used to interpret the separators within other:childpath. See Column Properties for more details. |
| other:childpath | The path to the attribute that is used to UNNEST the child table. Empty if not a child table. |
| Property | Meaning |
| name | Required. The name of the column, lower-cased. |
| key | Used to mark the primary key. Required for Document.Id but optional for other columns. |
| xs:type | Required. The type of the column within the connector. |
| other:iskey | Required. Must be the same value as key, or "false" if key is not included. |
| other:pathspec | Required. This is used to interpret the separators within other:field. |
| other:field | Required. The path to the field in Couchbase. |
{
"numeric_object": {
"0": 0
},
"array": [
0
]
}
To ensure that the connector can distinguish between field and array accesses, the pathspec is used to determine whether each "." in the field is an array or an object. Each "{" represents a field access, while each "[" represents an array access.
For example, with a field of "a.0.b.1" and a "pathspec" of "[{[", the N1QL expression "a[0].b[1]" would be generated. If instead the "pathspec" were "{{{", then the N1QL expression "a.`0`.b.`1`" would be generated.
This section contains a complete schema. Set the Location property to the file directory that will contain the schema file. The info section enables a relational view of a Couchbase object. For more details, see Custom Schema Definitions. The table below allows the SELECT, INSERT, UPDATE, and DELETE commands as implemented in the GET, POST, MERGE, and DELETE sections of the schema below. The operations, such as couchbaseadoSysData, are internal implementations.
<rsb:script xmlns:rsb="http://www.rssbus.com/ns/rsbscript/2">
<rsb:info title="Customers" description="Customers" other:dataverse="" other:bucket=customers"" other:flavorexpr="" other:flavorvalue="" other:isarray="false" other:pathspec="" other:childpath="">
<attr name="document.id" xs:type="string" key="true" other:iskey="true" other:pathspec="" />
<attr name="annual_revenue" xs:type="integer" other:iskey="false" other:pathspec="" other:field="annual_revenue" />
<attr name="homeaddress.city" xs:type="string" other:iskey="false" other:pathspec="{" other:field="homeaddress.city" />
<attr name="homeaddress.state" xs:type="string" other:iskey="false" other:pathspec="{" other:field="homeaddress.state" />
<attr name="homeaddress.street" xs:type="string" other:iskey="false" other:pathspec="{" other:field="homeaddress.street" />
<attr name="name" xs:type="string" other:iskey="false" other:pathspec="" other:field="name" />
<attr name="id" xs:type="integer" other:iskey="false" other:pathspec="" other:field="id" />
<attr name="offices" xs:type="string" other:iskey="false" other:pathspec="" other:field="offices" />
<attr name="offices.0" xs:type="string" other:iskey="false" other:pathspec="[" other:field="offices.0" />
<attr name="offices.1" xs:type="string" other:iskey="false" other:pathspec="[" other:field="offices.1" />
<attr name="workaddress.city" xs:type="string" other:iskey="false" other:pathspec="{" other:field="workaddress.city" />
<attr name="workaddress.state" xs:type="string" other:iskey="false" other:pathspec="{" other:field="workaddress.state" />
<attr name="workaddress.street" xs:type="string" other:iskey="false" other:pathspec="{" other:field="workaddress.street" />
</rsb:info>
</rsb:script>
This section details a selection of advanced features of the Couchbase connector.
The connector allows you to define virtual tables, called user defined views, whose contents are decided by a pre-configured query. These views are useful when you cannot directly control queries being issued to the drivers. See User Defined Views for an overview of creating and configuring custom views.
Use SSL Configuration to adjust how connector handles TLS/SSL certificate negotiations. You can choose from various certificate formats; see the SSLServerCert property under "Connection String Options" for more information.
To configure the connector using Private Agent proxy settings, select the Use Proxy Settings checkbox on the connection configuration screen.
The Jitterbit Connector for Couchbase allows you to define a virtual table whose contents are decided by a pre-configured query. These are called User Defined Views, which are useful in situations where you cannot directly control the query being issued to the driver, e.g. when using the driver from Jitterbit. The User Defined Views can be used to define predicates that are always applied. If you specify additional predicates in the query to the view, they are combined with the query already defined as part of the view.
There are two ways to create user defined views:User Defined Views are defined in a JSON-formatted configuration file called UserDefinedViews.json. The connector automatically detects the views specified in this file.
You can also have multiple view definitions and control them using the UserDefinedViews connection property. When you use this property, only the specified views are seen by the connector.
This User Defined View configuration file is formatted as follows:For example:
{
"MyView": {
"query": "SELECT * FROM Customer WHERE MyColumn = 'value'"
},
"MyView2": {
"query": "SELECT * FROM MyTable WHERE Id IN (1,2,3)"
}
}
Use the UserDefinedViews connection property to specify the location of your JSON configuration file. For example:
"UserDefinedViews", "C:\Users\yourusername\Desktop\tmp\UserDefinedViews.json"
SELECT * FROM Customers WHERE City = 'Raleigh';An example of a query to the driver:
SELECT * FROM UserViews.RCustomers WHERE Status = 'Active';Resulting in the effective query to the source:
SELECT * FROM Customers WHERE City = 'Raleigh' AND Status = 'Active';That is a very simple example of a query to a User Defined View that is effectively a combination of the view query and the view definition. It is possible to compose these queries in much more complex patterns. All SQL operations are allowed in both queries and are combined when appropriate.
By default, the connector attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store.
To specify another certificate, see the SSLServerCert property for the available formats to do so.
The Couchbase connector also supports setting client certificates. Set the following to connect using a client certificate.
Depending upon the connection settings being used, the connector can present several different mappings between Couchbase entities and relational tables and views. For more details on each of these capabilities, refer to the NoSQL portion of this documentation.
Please see the Automatic Schema Discovery section for more details on how flavor and child tables are exposed. In addition, the NewChildJoinsMode connection property is recommended for workflows that make heavy use of child tables. The documentation for that connection property details the improvements it makes to the connector data model.
Couchbase has different ways of grouping buckets and datasets depending on the CouchbaseService and version of Couchbase you are connecting to:
All of the schemas provided by the connector are dynamically retrieved from Couchbase, so any changes in the buckets or fields within Couchbase will be reflected in the connector the next time you connect. You may also issue a reset query to refresh schemas without having to close the connection:
RESET SCHEMA CACHE
NOTE: Stored procedures are not currently supported. See the above note for details.
Stored procedures* are available to complement the data available from the Data Model. It may be necessary to update data available from a view using a stored procedure* because the data does not provide for direct, table-like, two-way updates. In these situations, the retrieval of the data is done using the appropriate view or table, while the update is done by calling a stored procedure. Stored procedures* take a list of parameters and return back a dataset that contains the collection of tuples that constitute the response.
| Name | Description |
| AddDocument | Upsert entire JSON documents to Couchbase as-is. |
| CreateBucket | Creates a new bucket in CouchBase. |
| CreateCollection | Creates a collection under an existing scope |
| CreateSchema | Creates a schema definition of a table in Couchbase. Results may change depending of the value of FlattenObjects, FlattenArrays, and TypeDetectionScheme. |
| CreateScope | Creates a scope under an existing bucket |
| CreateUserTable | An internal operation used when GenerateSchemaFiles=OnCreate |
| DeleteBucket | Deletes a bucket (and all its collections and scopes, where supported) |
| DeleteCollection | Deletes a collection (Couchbase 7 and up) |
| DeleteScope | Deletes a scope and all its collections (Couchbase 7 and up) |
| FlushBucket | Removes all documents from a bucket in Couchbase. |
| ListIndices | Lists all indices available in Couchbase |
| ManageIndices | Creates/Drops an index in a target bucket in Couchbase. |
Upsert entire JSON documents to Couchbase as-is.
| Name | Type | Required | Description |
| BucketName | String | True | The bucket to insert the document into. |
| SourceTable | String | False | The name of the temp table containing ID and Document columns. Required if no ID is specified. |
| ID | String | False | The primary key to insert the document under. Required if no SourceTable is specified. |
| Document | String | False | The JSON text of the document to insert. Required if not SourceTable is specified. |
| Name | Type | Description |
| RowsAffected | String | The number of rows successfully updated |
Creates a new bucket in CouchBase.
Buckets using @AuthType 'none' can be created by specifying only the @Name, @AuthType, @BucketType, and @RamQuotaMB. The @ProxyPort option may also be required, depending upon what version of Couchbase you are connecting to.
EXECUTE CreateBucket @Name = 'Players', @AuthType = 'NONE', @BucketType = 'COUCHBASE', @RamQuotaMB = 100, @ProxyPort = 1234
When creating a bucket with @AuthType 'sasl', the @ProxyPort must not be provided, and the @SaslPassword is optional:
EXECUTE CreateBucket @Name = 'Players', @AuthType = 'SASL', @BucketType = 'COUCHBASE', @RamQuotaMB = 100
All other parameters can be used regardless of what @AuthType you provide.
| Name | Type | Required | Description |
| Name | String | True | The name of the bucket to create. |
| AuthType | String | True | The type of authentication to use can be sasl or none. |
| BucketType | String | True | The type of the bucket, can be memcached or couchbase. |
| EvictionPolicy | String | False | What to evict from the cache if the bucket is full, can be fullEviction or valueOnly |
| FlushEnabled | String | False | Enables or disables flush all support, can be 0 or 1. |
| ParallelDBAndViewCompaction | String | False | Enables simultaneous compactions of the database and the views, can be true or false. |
| ProxyPort | String | False | The proxy port, must be unused, required if authorization is not SASL. |
| RamQuotaMB | String | True | The amount of RAM to allocate to the bucket, in megabytes. |
| ReplicaIndex | String | False | Enables or disables replicate indexes, can be 1 or 0. |
| ReplicaNumber | String | False | A number between 0 and 3, specifies number of replicas. |
| SaslPassword | String | False | SASL password, may be provided if the authentication type is SASL. |
| ThreadsNumber | String | False | A number between 2 and 8, specifies number of concurrent readers/writers. |
| CompressionMode | String | False | Either Off (no compression), Passive (documents inserted compressed stay comressed) or Active (server can compress any document). On Couchbase Enterprise, Passive is the default. |
| ConflictResolutionType | String | False | How the server will resolve conflicts between cluster nodes. Either lww (timestamp-based resolution) or seqno (revision ID-based resolution). Defaults to seqno on Couchbase Enterprise. |
| Name | Type | Description |
| Success | String | Whether or not the bucket was successfully created. |
Creates a collection under an existing scope
| Name | Type | Required | Description |
| Bucket | String | True | The name of the bucket containing the collection. |
| Scope | String | True | The name of the scope containing the collection. |
| Name | String | True | The name of the collection to create. |
| Name | Type | Description |
| Success | Bool | Whether or not the collection was successfully created. |
Creates a schema definition of a table in Couchbase. Results may change depending of the value of FlattenObjects, FlattenArrays, and TypeDetectionScheme.
| Name | Type | Required | Description |
| TableName | String | True | The name of the table. |
| FileName | String | False | The full file path and name of the schema to generate, required if the location connection property is not set. Ex : 'C:\Users\User\Desktop\SmartSheet\sheet.rsd' |
| Overwrite | String | False | Will delete any existing schema file for this table. |
| Name | Type | Description |
| Result | String | Whether or not the schema was successfully built. |
Creates a scope under an existing bucket
| Name | Type | Required | Description |
| Bucket | String | True | The name of the bucket containing the scope. |
| Name | String | True | The name of the scope to create. |
| Name | Type | Description |
| Success | Bool | Whether or not the scope was successfully created. |
An internal operation used when GenerateSchemaFiles=OnCreate
Note: This procedure makes use of indexed parameters. These input parameters are denoted with a '#' character at the end of their names.
Indexed parameters facilitate providing multiple instances a single parameter as inputs for the procedure.
Suppose there is an input parameter named Param#. Input multiple instances of an indexed parameter like this:
EXEC ProcedureName Param#1 = "value1", Param#2 = "value2", Param#3 = "value3"
| Name | Type | Required | Description |
| CreateNotExist | String | False | Whether an existing table is an error or not |
| TableName | String | False | The name of the table to create |
| ColumnNames# | String | False | For each column, its name |
| ColumnDataTypes# | String | False | For each column, its type |
| ColumnSizes# | String | False | For each column, its size (ignored) |
| ColumnScales# | String | False | For each column, its scale (ignored) |
| ColumnIsNulls# | String | False | For each column, whether it allows NULLs (ignored) |
| ColumnDefaults# | String | False | For each column, its default value (ignored) |
| Location | String | False | Where the schema file is generated |
| Name | Type | Description |
| AffectedTables | String | The number of tables created, either 0 or 1 |
Deletes a bucket (and all its collections and scopes, where supported)
| Name | Type | Required | Description |
| Name | String | True | The name of the bucket to delete. |
| Name | Type | Description |
| Success | Bool | Whether or not the bucket was successfully deleted. |
Deletes a collection (Couchbase 7 and up)
| Name | Type | Required | Description |
| Bucket | String | True | The name of the bucket containing the collection. |
| Scope | String | True | The name of the scope containing the collection. |
| Name | String | True | The name of the collection to delete. |
| Name | Type | Description |
| Success | Bool | Whether or not the collection was successfully deleted. |
Deletes a scope and all its collections (Couchbase 7 and up)
| Name | Type | Required | Description |
| Bucket | String | True | The name of the bucket containing the scope. |
| Name | String | True | The name of the scope to delete. |
| Name | Type | Description |
| Success | Bool | Whether or not the scope was successfully deleted. |
Removes all documents from a bucket in Couchbase.
| Name | Type | Required | Description |
| Name | String | True | The name of the bucket to delete. Flush must be enabled on this bucket. |
| Name | Type | Description |
| Success | Bool | Whether or not the bucket was successfully flushed. |
Lists all indices available in Couchbase
| Name | Type | Description |
| Id | String | The unique index ID |
| Datastore_id | String | The server hosting the indexed bucket |
| Namespace_id | String | The pool hosting the indexed bucket |
| Bucket_id | String | The bucket the index applies to if the index applies to a collection (Couchbase 7 and up). NULL otherwise. |
| Scope_id | String | The scope the index applies to if the index applies to a collection (Couchbase 7 and up). NULL otherwise. |
| Keyspace_id | String | The collection the index applies to, if the index applis to a collection (Couchbase 7 and up). The bucket the index applies to otherwise. |
| Index_key | String | A list of keys participating in the index |
| Condition | String | The N1QL filter that the index applies to |
| Is_primary | String | Whether the index is on the primary key |
| Name | String | The name of the index |
| State | String | Whether the index is available |
| Using | String | Whether the index is backed by GSI or a view |
Creates/Drops an index in a target bucket in Couchbase.
An anonymous primary index can be created with these parameters:
EXECUTE ManageIndices @BucketName = 'Players' @Action = 'CREATE' @IsPrimary = 'true' @IndexType = 'VIEW'
This is the same as executing this N1QL:
CREATE PRIMARY INDEX ON `Players` USING VIEW
A named primary index can be created by specifying an @Name, in addition to the parameters listed above:
EXECUTE ManageIndices @BucketName = 'Players' @Action = 'CREATE' @IsPrimary = 'true' @Name = 'Players_primary' @IndexType = 'VIEW'
A secondary index can be created by setting @IsPrimary to false and providing at least one expression.
EXECUTE ManageIndices @BucketName = 'Players', @Action = 'CREATE', @IsPrimary = 'false', @Name = 'Players_playtime_score', @Expressions = '["score", "playtime"]'
This is the same as running the following N1QL:
CREATE INDEX `Players_playtime_score` ON `Players`(score, playtime) USING GSI;
Multiple nodes and filters can also be provied to generate more complex indices. They must be provided as JSON lists:
EXECUTE ManageIndices @BucketName = 'Players', @Name = 'TopPlayers', @Expressions = '["score", "playtime"]', @Filter = '["topscore > 1000", "playtime > 600"]', @Nodes = '["127.0.0.1:8091", "192.168.0.100:8091"]'
This is the same as running the following N1QL:
CREATE INDEX `TopPlayers` ON `Players`(score, playtime) WHERE topscore > 1000 AND playtime > 600 USING GSI WITH { "nodes": ["127.0.0.1:8091", "192.168.0.100:8091"]};
| Name | Type | Required | Description |
| BucketName | String | True | The target bucket to create or drop the the index from. |
| ScopeName | String | False | The target scope to create or drop the index from (Couchbase 7 and up) |
| CollectionName | String | False | The target collection to create or drop the index from (Couchbase 7 and up) |
| Action | String | True | Specifies which action to perform on the index, can be Create or Drop. |
| Expressions | String | False | A list of expressions or functions, encoded as JSON, that the index will be based off of. At least one is required if IsPrimary is set to false and the action is Create. |
| Name | String | False | The name of the index to create or drop, required if IsPrimary is set to false. |
| IsPrimary | String | False | Specifies wether the index should be a primary index.
The default value is true. |
| Filters | String | False | A list of filters, encoded as JSON, to apply on the index. |
| IndexType | String | False | The type of index to create, can be GSI or View, only used if the action is Create.
The default value is GSI. |
| ViewName | String | False | Deprecated, included for compatibility only. Does nothing. |
| Nodes | String | False | A list, encoded as JSON, of nodes to contain the index, must contain the port. Only used if the action is Create. |
| NumReplica | String | False | How many replicas to create among the index nodes in the cluster. |
| Name | Type | Description |
| Success | String | Whether or not the index was successfully created or dropped. |
You can query the system tables described in this section to access schema information, information on data source functionality, and batch operation statistics.
The following tables return database metadata for Couchbase:
The following tables return information about how to connect to and query the data source:
The following table returns query statistics for data modification queries:
Lists the available databases.
The following query retrieves all databases determined by the connection string:
SELECT * FROM sys_catalogs
| Name | Type | Description |
| CatalogName | String | The database name. |
Lists the available schemas.
The following query retrieves all available schemas:
SELECT * FROM sys_schemas
| Name | Type | Description |
| CatalogName | String | The database name. |
| SchemaName | String | The schema name. |
Lists the available tables.
The following query retrieves the available tables and views:
SELECT * FROM sys_tables
| Name | Type | Description |
| CatalogName | String | The database containing the table or view. |
| SchemaName | String | The schema containing the table or view. |
| TableName | String | The name of the table or view. |
| TableType | String | The table type (table or view). |
| Description | String | A description of the table or view. |
| IsUpdateable | Boolean | Whether the table can be updated. |
Describes the columns of the available tables and views.
The following query returns the columns and data types for the Customer table:
SELECT ColumnName, DataTypeName FROM sys_tablecolumns WHERE TableName='Customer'
| Name | Type | Description |
| CatalogName | String | The name of the database containing the table or view. |
| SchemaName | String | The schema containing the table or view. |
| TableName | String | The name of the table or view containing the column. |
| ColumnName | String | The column name. |
| DataTypeName | String | The data type name. |
| DataType | Int32 | An integer indicating the data type. This value is determined at run time based on the environment. |
| Length | Int32 | The storage size of the column. |
| DisplaySize | Int32 | The designated column's normal maximum width in characters. |
| NumericPrecision | Int32 | The maximum number of digits in numeric data. The column length in characters for character and date-time data. |
| NumericScale | Int32 | The column scale or number of digits to the right of the decimal point. |
| IsNullable | Boolean | Whether the column can contain null. |
| Description | String | A brief description of the column. |
| Ordinal | Int32 | The sequence number of the column. |
| IsAutoIncrement | String | Whether the column value is assigned in fixed increments. |
| IsGeneratedColumn | String | Whether the column is generated. |
| IsHidden | Boolean | Whether the column is hidden. |
| IsArray | Boolean | Whether the column is an array. |
Lists the available stored procedures.
The following query retrieves the available stored procedures:
SELECT * FROM sys_procedures
| Name | Type | Description |
| CatalogName | String | The database containing the stored procedure. |
| SchemaName | String | The schema containing the stored procedure. |
| ProcedureName | String | The name of the stored procedure. |
| Description | String | A description of the stored procedure. |
| ProcedureType | String | The type of the procedure, such as PROCEDURE or FUNCTION. |
Describes stored procedure* parameters.
The following query returns information about all of the input parameters for the SelectEntries stored procedure:
SELECT * FROM sys_procedureparameters WHERE ProcedureName='SelectEntries' AND Direction=1 OR Direction=2
| Name | Type | Description |
| CatalogName | String | The name of the database containing the stored procedure. |
| SchemaName | String | The name of the schema containing the stored procedure. |
| ProcedureName | String | The name of the stored procedure* containing the parameter. |
| ColumnName | String | The name of the stored procedure* parameter. |
| Direction | Int32 | An integer corresponding to the type of the parameter: input (1), input/output (2), or output(4). input/output type parameters can be both input and output parameters. |
| DataTypeName | String | The name of the data type. |
| DataType | Int32 | An integer indicating the data type. This value is determined at run time based on the environment. |
| Length | Int32 | The number of characters allowed for character data. The number of digits allowed for numeric data. |
| NumericPrecision | Int32 | The maximum precision for numeric data. The column length in characters for character and date-time data. |
| NumericScale | Int32 | The number of digits to the right of the decimal point in numeric data. |
| IsNullable | Boolean | Whether the parameter can contain null. |
| IsRequired | Boolean | Whether the parameter is required for execution of the procedure. |
| IsArray | Boolean | Whether the parameter is an array. |
| Description | String | The description of the parameter. |
| Ordinal | Int32 | The index of the parameter. |
Describes the primary and foreign keys. The following query retrieves the primary key for the Customer table:
SELECT * FROM sys_keycolumns WHERE IsKey='True' AND TableName='Customer'
| Name | Type | Description |
| CatalogName | String | The name of the database containing the key. |
| SchemaName | String | The name of the schema containing the key. |
| TableName | String | The name of the table containing the key. |
| ColumnName | String | The name of the key column. |
| IsKey | Boolean | Whether the column is a primary key in the table referenced in the TableName field. |
| IsForeignKey | Boolean | Whether the column is a foreign key referenced in the TableName field. |
| PrimaryKeyName | String | The name of the primary key. |
| ForeignKeyName | String | The name of the foreign key. |
| ReferencedCatalogName | String | The database containing the primary key. |
| ReferencedSchemaName | String | The schema containing the primary key. |
| ReferencedTableName | String | The table containing the primary key. |
| ReferencedColumnName | String | The column name of the primary key. |
Describes the foreign keys. The following query retrieves all foreign keys which refer to other tables:
SELECT * FROM sys_foreignkeys WHERE ForeignKeyType = 'FOREIGNKEY_TYPE_IMPORT'
| Name | Type | Description |
| CatalogName | String | The name of the database containing the key. |
| SchemaName | String | The name of the schema containing the key. |
| TableName | String | The name of the table containing the key. |
| ColumnName | String | The name of the key column. |
| PrimaryKeyName | String | The name of the primary key. |
| ForeignKeyName | String | The name of the foreign key. |
| ReferencedCatalogName | String | The database containing the primary key. |
| ReferencedSchemaName | String | The schema containing the primary key. |
| ReferencedTableName | String | The table containing the primary key. |
| ReferencedColumnName | String | The column name of the primary key. |
| ForeignKeyType | String | Designates whether the foreign key is an import (points to other tables) or export (referenced from other tables) key. |
Describes the available indexes. By filtering on indexes, you can write more selective queries with faster query response times.
The following query retrieves all indexes that are not primary keys:
SELECT * FROM sys_indexes WHERE IsPrimary='false'
| Name | Type | Description |
| CatalogName | String | The name of the database containing the index. |
| SchemaName | String | The name of the schema containing the index. |
| TableName | String | The name of the table containing the index. |
| IndexName | String | The index name. |
| ColumnName | String | The name of the column associated with the index. |
| IsUnique | Boolean | True if the index is unique. False otherwise. |
| IsPrimary | Boolean | True if the index is a primary key. False otherwise. |
| Type | Int16 | An integer value corresponding to the index type: statistic (0), clustered (1), hashed (2), or other (3). |
| SortOrder | String | The sort order: A for ascending or D for descending. |
| OrdinalPosition | Int16 | The sequence number of the column in the index. |
Returns information on the available connection properties and those set in the connection string.
When querying this table, the config connection string should be used:
jdbc:cdata:couchbase:config:
This connection string enables you to query this table without a valid connection.
The following query retrieves all connection properties that have been set in the connection string or set through a default value:
SELECT * FROM sys_connection_props WHERE Value <> ''
| Name | Type | Description |
| Name | String | The name of the connection property. |
| ShortDescription | String | A brief description. |
| Type | String | The data type of the connection property. |
| Default | String | The default value if one is not explicitly set. |
| Values | String | A comma-separated list of possible values. A validation error is thrown if another value is specified. |
| Value | String | The value you set or a preconfigured default. |
| Required | Boolean | Whether the property is required to connect. |
| Category | String | The category of the connection property. |
| IsSessionProperty | String | Whether the property is a session property, used to save information about the current connection. |
| Sensitivity | String | The sensitivity level of the property. This informs whether the property is obfuscated in logging and authentication forms. |
| PropertyName | String | A camel-cased truncated form of the connection property name. |
| Ordinal | Int32 | The index of the parameter. |
| CatOrdinal | Int32 | The index of the parameter category. |
| Hierarchy | String | Shows dependent properties associated that need to be set alongside this one. |
| Visible | Boolean | Informs whether the property is visible in the connection UI. |
| ETC | String | Various miscellaneous information about the property. |
Describes the SELECT query processing that the connector can offload to the data source.
When working with data sources that do not support SQL-92, you can query the sys_sqlinfo view to determine the query capabilities of the underlying APIs, expressed in SQL syntax.
Below is an example data set of SQL capabilities. Some aspects of SELECT functionality are returned in a comma-separated list if supported; otherwise, the column contains NO.
| Name | Description | Possible Values |
| AGGREGATE_FUNCTIONS | Supported aggregation functions. | AVG, COUNT, MAX, MIN, SUM, DISTINCT |
| COUNT | Whether COUNT function is supported. | YES, NO |
| IDENTIFIER_QUOTE_OPEN_CHAR | The opening character used to escape an identifier. | [ |
| IDENTIFIER_QUOTE_CLOSE_CHAR | The closing character used to escape an identifier. | ] |
| SUPPORTED_OPERATORS | A list of supported SQL operators. | =, >, <, >=, <=, <>, !=, LIKE, NOT LIKE, IN, NOT IN, IS NULL, IS NOT NULL, AND, OR |
| GROUP_BY | Whether GROUP BY is supported, and, if so, the degree of support. | NO, NO_RELATION, EQUALS_SELECT, SQL_GB_COLLATE |
| STRING_FUNCTIONS | Supported string functions. | LENGTH, CHAR, LOCATE, REPLACE, SUBSTRING, RTRIM, LTRIM, RIGHT, LEFT, UCASE, SPACE, SOUNDEX, LCASE, CONCAT, ASCII, REPEAT, OCTET, BIT, POSITION, INSERT, TRIM, UPPER, REGEXP, LOWER, DIFFERENCE, CHARACTER, SUBSTR, STR, REVERSE, PLAN, UUIDTOSTR, TRANSLATE, TRAILING, TO, STUFF, STRTOUUID, STRING, SPLIT, SORTKEY, SIMILAR, REPLICATE, PATINDEX, LPAD, LEN, LEADING, KEY, INSTR, INSERTSTR, HTML, GRAPHICAL, CONVERT, COLLATION, CHARINDEX, BYTE |
| NUMERIC_FUNCTIONS | Supported numeric functions. | ABS, ACOS, ASIN, ATAN, ATAN2, CEILING, COS, COT, EXP, FLOOR, LOG, MOD, SIGN, SIN, SQRT, TAN, PI, RAND, DEGREES, LOG10, POWER, RADIANS, ROUND, TRUNCATE |
| TIMEDATE_FUNCTIONS | Supported date/time functions. | NOW, CURDATE, DAYOFMONTH, DAYOFWEEK, DAYOFYEAR, MONTH, QUARTER, WEEK, YEAR, CURTIME, HOUR, MINUTE, SECOND, TIMESTAMPADD, TIMESTAMPDIFF, DAYNAME, MONTHNAME, CURRENT_DATE, CURRENT_TIME, CURRENT_TIMESTAMP, EXTRACT |
| REPLICATION_SKIP_TABLES | Indicates tables skipped during replication. | |
| REPLICATION_TIMECHECK_COLUMNS | A string array containing a list of columns which will be used to check for (in the given order) to use as a modified column during replication. | |
| IDENTIFIER_PATTERN | String value indicating what string is valid for an identifier. | |
| SUPPORT_TRANSACTION | Indicates if the provider supports transactions such as commit and rollback. | YES, NO |
| DIALECT | Indicates the SQL dialect to use. | |
| KEY_PROPERTIES | Indicates the properties which identify the uniform database. | |
| SUPPORTS_MULTIPLE_SCHEMAS | Indicates if multiple schemas may exist for the provider. | YES, NO |
| SUPPORTS_MULTIPLE_CATALOGS | Indicates if multiple catalogs may exist for the provider. | YES, NO |
| DATASYNCVERSION | The Data Sync version needed to access this driver. | Standard, Starter, Professional, Enterprise |
| DATASYNCCATEGORY | The Data Sync category of this driver. | Source, Destination, Cloud Destination |
| SUPPORTSENHANCEDSQL | Whether enhanced SQL functionality beyond what is offered by the API is supported. | TRUE, FALSE |
| SUPPORTS_BATCH_OPERATIONS | Whether batch operations are supported. | YES, NO |
| SQL_CAP | All supported SQL capabilities for this driver. | SELECT, INSERT, DELETE, UPDATE, TRANSACTIONS, ORDERBY, OAUTH, ASSIGNEDID, LIMIT, LIKE, BULKINSERT, COUNT, BULKDELETE, BULKUPDATE, GROUPBY, HAVING, AGGS, OFFSET, REPLICATE, COUNTDISTINCT, JOINS, DROP, CREATE, DISTINCT, INNERJOINS, SUBQUERIES, ALTER, MULTIPLESCHEMAS, GROUPBYNORELATION, OUTERJOINS, UNIONALL, UNION, UPSERT, GETDELETED, CROSSJOINS, GROUPBYCOLLATE, MULTIPLECATS, FULLOUTERJOIN, MERGE, JSONEXTRACT, BULKUPSERT, SUM, SUBQUERIESFULL, MIN, MAX, JOINSFULL, XMLEXTRACT, AVG, MULTISTATEMENTS, FOREIGNKEYS, CASE, LEFTJOINS, COMMAJOINS, WITH, LITERALS, RENAME, NESTEDTABLES, EXECUTE, BATCH, BASIC, INDEX |
| PREFERRED_CACHE_OPTIONS | A string value specifies the preferred cacheOptions. | |
| ENABLE_EF_ADVANCED_QUERY | Indicates if the driver directly supports advanced queries coming from Entity Framework. If not, queries will be handled client side. | YES, NO |
| PSEUDO_COLUMNS | A string array indicating the available pseudo columns. | |
| MERGE_ALWAYS | If the value is true, The Merge Mode is forcibly executed in Data Sync. | TRUE, FALSE |
| REPLICATION_MIN_DATE_QUERY | A select query to return the replicate start datetime. | |
| REPLICATION_MIN_FUNCTION | Allows a provider to specify the formula name to use for executing a server side min. | |
| REPLICATION_START_DATE | Allows a provider to specify a replicate startdate. | |
| REPLICATION_MAX_DATE_QUERY | A select query to return the replicate end datetime. | |
| REPLICATION_MAX_FUNCTION | Allows a provider to specify the formula name to use for executing a server side max. | |
| IGNORE_INTERVALS_ON_INITIAL_REPLICATE | A list of tables which will skip dividing the replicate into chunks on the initial replicate. | |
| CHECKCACHE_USE_PARENTID | Indicates whether the CheckCache statement should be done against the parent key column. | TRUE, FALSE |
| CREATE_SCHEMA_PROCEDURES | Indicates stored procedures* that can be used for generating schema files. |
SELECT * FROM sys_sqlinfo WHERE Name='SUPPORTED_OPERATORS'
Note that individual tables may have different limitations or requirements on the WHERE clause; refer to the Data Model section for more information.
| Name | Type | Description |
| NAME | String | A component of SQL syntax, or a capability that can be processed on the server. |
| VALUE | String | Detail on the supported SQL or SQL syntax. |
Returns information about attempted modifications.
The following query retrieves the Ids of the modified rows in a batch operation:
SELECT * FROM sys_identity
| Name | Type | Description |
| Id | String | The database-generated ID returned from a data modification operation. |
| Batch | String | An identifier for the batch. 1 for a single operation. |
| Operation | String | The result of the operation in the batch: INSERTED, UPDATED, or DELETED. |
| Message | String | SUCCESS or an error message if the update in the batch failed. |
The advanced configurations properties are the various options that can be used to establish a connection. This section provides a complete list of the options you can configure. Click the links for further details.
| Property | Description |
| AuthScheme | The type of authentication to use when connecting to Couchbase. |
| User | The Couchbase user account used to authenticate. |
| Password | The password used to authenticate the user. |
| CredentialsFile | Use this property if you need to provide credentials for multiple users or buckets. This file takes priority over other forms of authentication. |
| Server | The address of the Couchbase server or servers to which you are connecting. |
| CouchbaseService | Determines the Couchbase service to connect to. Default is N1QL. Available options are N1QL and Analytics. |
| ConnectionMode | Determines how to connect to the Couchbase server. Must be either Direct or Cloud. |
| DNSServer | Determines what DNS server to use when retrieving Couchbase Cloud information. |
| N1QLPort | The port for connecting to the Couchbase N1QL Endpoint. |
| AnalyticsPort | The port for connecting to the Couchbase Analytics Endpoint. |
| WebConsolePort | The port for connecting to the Couchbase Web Console. |
| Property | Description |
| SSLClientCert | The TLS/SSL client certificate store for SSL Client Authentication (2-way SSL). |
| SSLClientCertType | The type of key store containing the TLS/SSL client certificate. |
| SSLClientCertPassword | The password for the TLS/SSL client certificate. |
| SSLClientCertSubject | The subject of the TLS/SSL client certificate. |
| UseSSL | Whether to negotiate TLS/SSL when connecting to the Couchbase server. |
| SSLServerCert | The certificate to be accepted from the server when connecting using TLS/SSL. |
| Property | Description |
| Location | A path to the directory that contains the schema files defining tables, views, and stored procedures. |
| BrowsableSchemas | This property restricts the schemas reported to a subset of the available schemas. For example, BrowsableSchemas=SchemaA, SchemaB, SchemaC. |
| Tables | This property restricts the tables reported to a subset of the available tables. For example, Tables=TableA, TableB, TableC. |
| Views | Restricts the views reported to a subset of the available tables. For example, Views=ViewA, ViewB, ViewC. |
| Dataverse | Which Analytics dataverse to scan when discovering tables. |
| TypeDetectionScheme | Determines how the provider builds tables and columns from the buckets found in Couchbase. |
| InferNumSampleValues | The maximum number of values for every field to scan before determining its data type. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER. |
| InferSampleSize | The maximum number of documents to scan for the columns available in the bucket. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER. |
| InferSimilarityMetric | Specifies the similarity degree where different schemas will be considered to be the same flavor. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER. |
| FlexibleSchemas | Whether the provider allows queries to use columns that it has not discovered. |
| ExposeTTL | Specifies whether document TTL information should be exposed. |
| NumericStrings | Whether to allow string values to be treated as numbers. |
| IgnoreChildAggregates | Whether the provider exposes aggregate columns that are also available as child tables. Ignored if TableSupport is not set to Full. |
| TableSupport | How much effort the provider will put into discovering tables on the Couchbase server. |
| NewChildJoinsMode | Determines the kind of child table model the provider exposes. |
| Property | Description |
| AllowJSONParameters | Allows raw JSON to be used in parameters when QueryPassthrough is enabled. |
| ChildSeparator | The character or characters used to denote child tables. |
| CreateTableRamQuota | The default RAM quota, in megabytes, to use when inserting buckets via the CREATE TABLE syntax. |
| DataverseSeparator | The character or characters used to denote Analytics dataverses and scopes/collections. |
| FlattenArrays | The number of elements to expose as columns from nested arrays. Ignored if IgnoreChildAggregates is enabled. |
| FlattenObjects | Set FlattenObjects to true to flatten object properties into columns of their own. Otherwise, objects nested in arrays are returned as strings of JSON. |
| FlavorSeparator | The character or characters used to denote flavors. |
| GenerateSchemaFiles | Indicates the user preference as to when schemas should be generated and saved. |
| InsertNullValues | Determines whether an INSERT should include fields that have NULL values. |
| MaxRows | Limits the number of rows returned rows when no aggregation or group by is used in the query. This helps avoid performance issues at design time. |
| Other | These hidden properties are used only in specific use cases. |
| Pagesize | The maximum number of results to return per page from Couchbase. |
| PeriodsSeparator | The character or characters used to denote hierarchy. |
| PseudoColumns | This property indicates whether or not to include pseudo columns as columns to the table. |
| QueryExecutionTimeout | This sets the server-side timeout for the query, which governs how long Couchbase will execute the query before returning a timeout error. |
| QueryPassthrough | This option passes the query to the Couchbase server as is. |
| RowScanDepth | The maximum number of rows to scan to look for the columns available in a table. |
| StrictComparison | Adjusts how precisely to translate filters on SQL input queries into Couchbase queries. This can be set to a comma-separated list of values, where each value can be one of: date, number, boolean, or string. |
| Timeout | The value in seconds until the timeout error is thrown, canceling the operation. |
| TransactionDurability | Specifies how a document must be stored for a transaction to succeed. Specifies whether to use N1QL transactions when executing queries. |
| TransactionTimeout | This sets the amount of time a transaction may execute before it is timed out by Couchbase. |
| UpdateNullValues | Determines whether an UPDATE writes NULL values as NULL, or removes them. |
| UseCollectionsForDDL | Whether to assume that CREATE TABLE statements use collections instead of flavors. Only takes effect when connecting to Couchbase v7+ and GenerateSchemaFiles is set to OnCreate. |
| UseTransactions | Specifies whether to use N1QL transactions when executing queries. |
| ValidateJSONParameters | Allows the provider to validate that string parameters are valid JSON before sending the query to Couchbase. |
This section provides a complete list of authentication properties you can configure.
| Property | Description |
| AuthScheme | The type of authentication to use when connecting to Couchbase. |
| User | The Couchbase user account used to authenticate. |
| Password | The password used to authenticate the user. |
| CredentialsFile | Use this property if you need to provide credentials for multiple users or buckets. This file takes priority over other forms of authentication. |
| Server | The address of the Couchbase server or servers to which you are connecting. |
| CouchbaseService | Determines the Couchbase service to connect to. Default is N1QL. Available options are N1QL and Analytics. |
| ConnectionMode | Determines how to connect to the Couchbase server. Must be either Direct or Cloud. |
| DNSServer | Determines what DNS server to use when retrieving Couchbase Cloud information. |
| N1QLPort | The port for connecting to the Couchbase N1QL Endpoint. |
| AnalyticsPort | The port for connecting to the Couchbase Analytics Endpoint. |
| WebConsolePort | The port for connecting to the Couchbase Web Console. |
The type of authentication to use when connecting to Couchbase.
string
"Auto"
Note that only Basic authentication is supported when using the Cloud ConnectionMode.
The Couchbase user account used to authenticate.
string
""
Together with Password, this field is used to authenticate against the Couchbase server.
The password used to authenticate the user.
string
""
The User and Password are together used to authenticate with the server.
Use this property if you need to provide credentials for multiple users or buckets. This file takes priority over other forms of authentication.
string
""
Use this property if you need to provide credentials for multiple users or buckets. This takes priority over other forms of authentication.
Set CredentialsFile to the path to a file that has the same markup as below:
[{"user": "YourUserName1", "pass":"YourPassword1"},
{"user": "YourUserName2", "pass":"YourPassword2"}]
The address of the Couchbase server or servers to which you are connecting.
string
""
This value can be set to a hostname or an IP address, like "couchbase-server.com" or "1.2.3.4". It can also be set to an HTTP or HTTPS URL, such as "https://couchbase-server.com" or "http://1.2.3.4". If ConnectionMode is set to Cloud then this should be the hostname of the Couchbase Cloud instance as reported in the control panel.
If the URL form is used, then setting this option will also set the UseSSL option: if the URL scheme is "https://", then UseSSL will be set to true, and a URL with "http://" will set UseSSL to false.
A port value cannot be used as part of this option, so values like "http://couchbase-server.com:8093" are not allowed. Please use WebConsolePort, N1QLPort and AnalyticsPort.
This value can also accept multiple servers in the above format separated by commas, such as "1.2.3.4, couchbase-server.com". This will allow the connector to recover the connection in case some of the servers listed are inaccessible.
Note that while the connector will try to recover the connection as a whole, it may lose individual operations. For example, while a long-running query will fail if the server becomes inaccesssible while that query is running, that query can be retried on the same connection and the connector will execute it on the next active server.
Determines the Couchbase service to connect to. Default is N1QL. Available options are N1QL and Analytics.
string
"N1QL"
Determines the Couchbase service to connect to. Default is N1QL. Available options are N1QL and Analytics
Determines how to connect to the Couchbase server. Must be either Direct or Cloud.
string
"Direct"
By default the connector connects to Couchbase directly using the address given in the Server option. The Server must be running the appropriate CouchbaseService to accept the connection. This will work in most on-premise or basic cloud deployments.
This should be set to Cloud when connecting to Couchbase Cloud or a custom deployment that uses service records. These records will allow the connector to determine the exact Couchbase servers that provide the appropriate CouchbaseService. You must also set the DNSServer property so that the connector is able to fetch these service records.
Note that enabling Cloud mode will override these connection properties with the values discovered by contacting the cluster:
Determines what DNS server to use when retrieving Couchbase Cloud information.
string
""
In most cases any public DNS server can be provided here such as the ones provided by OpenDNS, Cloudflare or Google.
If these are not accessible then you will need to use the DNS server configured by your network administrator.
The port for connecting to the Couchbase N1QL Endpoint.
string
""
This defaults to 8093 when not using SSL, and 18093 when using SSL. See UseSSL.
This port is used for submitting queries when CouchbaseService is set to N1QL. Any requests to manage indices will also go through this port.
The port for connecting to the Couchbase Analytics Endpoint.
string
""
This defaults to 8095 when not using SSL, and 18095 when using SSL. See UseSSL.
This port is used for submitting queries when CouchbaseService is set to Analytics.
The port for connecting to the Couchbase Web Console.
string
""
This defaults to 8091 when not using SSL, and 18091 when using SSL. See UseSSL.
This port is used for API operations like managing buckets.
This section provides a complete list of SSL properties you can configure.
| Property | Description |
| SSLClientCert | The TLS/SSL client certificate store for SSL Client Authentication (2-way SSL). |
| SSLClientCertType | The type of key store containing the TLS/SSL client certificate. |
| SSLClientCertPassword | The password for the TLS/SSL client certificate. |
| SSLClientCertSubject | The subject of the TLS/SSL client certificate. |
| UseSSL | Whether to negotiate TLS/SSL when connecting to the Couchbase server. |
| SSLServerCert | The certificate to be accepted from the server when connecting using TLS/SSL. |
The TLS/SSL client certificate store for SSL Client Authentication (2-way SSL).
string
""
The name of the certificate store for the client certificate.
The SSLClientCertType field specifies the type of the certificate store specified by SSLClientCert. If the store is password protected, specify the password in SSLClientCertPassword.
SSLClientCert is used in conjunction with the SSLClientCertSubject field in order to specify client certificates. If SSLClientCert has a value, and SSLClientCertSubject is set, a search for a certificate is initiated. See SSLClientCertSubject for more information.
Designations of certificate stores are platform-dependent.
The following are designations of the most common User and Machine certificate stores in Windows:
| MY | A certificate store holding personal certificates with their associated private keys. |
| CA | Certifying authority certificates. |
| ROOT | Root certificates. |
| SPC | Software publisher certificates. |
In Java, the certificate store normally is a file containing certificates and optional private keys.
When the certificate store type is PFXFile, this property must be set to the name of the file. When the type is PFXBlob, the property must be set to the binary contents of a PFX file (for example, PKCS12 certificate store).
The type of key store containing the TLS/SSL client certificate.
string
"USER"
This property can take one of the following values:
| USER - default | For Windows, this specifies that the certificate store is a certificate store owned by the current user. Note that this store type is not available in Java. |
| MACHINE | For Windows, this specifies that the certificate store is a machine store. Note that this store type is not available in Java. |
| PFXFILE | The certificate store is the name of a PFX (PKCS12) file containing certificates. |
| PFXBLOB | The certificate store is a string (base-64-encoded) representing a certificate store in PFX (PKCS12) format. |
| JKSFILE | The certificate store is the name of a Java key store (JKS) file containing certificates. Note that this store type is only available in Java. |
| JKSBLOB | The certificate store is a string (base-64-encoded) representing a certificate store in JKS format. Note that this store type is only available in Java. |
| PEMKEY_FILE | The certificate store is the name of a PEM-encoded file that contains a private key and an optional certificate. |
| PEMKEY_BLOB | The certificate store is a string (base64-encoded) that contains a private key and an optional certificate. |
| PUBLIC_KEY_FILE | The certificate store is the name of a file that contains a PEM- or DER-encoded public key certificate. |
| PUBLIC_KEY_BLOB | The certificate store is a string (base-64-encoded) that contains a PEM- or DER-encoded public key certificate. |
| SSHPUBLIC_KEY_FILE | The certificate store is the name of a file that contains an SSH-style public key. |
| SSHPUBLIC_KEY_BLOB | The certificate store is a string (base-64-encoded) that contains an SSH-style public key. |
| P7BFILE | The certificate store is the name of a PKCS7 file containing certificates. |
| PPKFILE | The certificate store is the name of a file that contains a PuTTY Private Key (PPK). |
| XMLFILE | The certificate store is the name of a file that contains a certificate in XML format. |
| XMLBLOB | The certificate store is a string that contains a certificate in XML format. |
The password for the TLS/SSL client certificate.
string
""
If the certificate store is of a type that requires a password, this property is used to specify that password to open the certificate store.
The subject of the TLS/SSL client certificate.
string
"*"
When loading a certificate the subject is used to locate the certificate in the store.
If an exact match is not found, the store is searched for subjects containing the value of the property. If a match is still not found, the property is set to an empty string, and no certificate is selected.
The special value "*" picks the first certificate in the certificate store.
The certificate subject is a comma separated list of distinguished name fields and values. For example, "CN=www.server.com, OU=test, C=US, E=support@company.com". The common fields and their meanings are shown below.
| Field | Meaning |
| CN | Common Name. This is commonly a host name like www.server.com. |
| O | Organization |
| OU | Organizational Unit |
| L | Locality |
| S | State |
| C | Country |
| E | Email Address |
If a field value contains a comma, it must be quoted.
Whether to negotiate TLS/SSL when connecting to the Couchbase server.
bool
false
When this is set to true, the defaults for the following options change:
| Property | Plaintext Default | SSL Default |
| AnalyticsPort | 8095 | 18095 |
| N1QLPort | 8093 | 18093 |
| WebConsolePort | 8091 | 18091 |
This option should be enabled when connecting to Couchbase Cloud because all Couchbase Cloud deployments use SSL by default.
The certificate to be accepted from the server when connecting using TLS/SSL.
string
""
If using a TLS/SSL connection, this property can be used to specify the TLS/SSL certificate to be accepted from the server. Any other certificate that is not trusted by the machine is rejected.
This property can take the following forms:
| Description | Example |
| A full PEM Certificate (example shortened for brevity) | -----BEGIN CERTIFICATE----- MIIChTCCAe4CAQAwDQYJKoZIhv......Qw== -----END CERTIFICATE----- |
| A path to a local file containing the certificate | C:\cert.cer |
| The public key (example shortened for brevity) | -----BEGIN RSA PUBLIC KEY----- MIGfMA0GCSq......AQAB -----END RSA PUBLIC KEY----- |
| The MD5 Thumbprint (hex values can also be either space or colon separated) | ecadbdda5a1529c58a1e9e09828d70e4 |
| The SHA1 Thumbprint (hex values can also be either space or colon separated) | 34a929226ae0819f2ec14b4a3d904f801cbb150d |
If not specified, any certificate trusted by the machine is accepted.
Certificates are validated as trusted by the machine based on the System's trust store. The trust store used is the 'javax.net.ssl.trustStore' value specified for the system. If no value is specified for this property, Java's default trust store is used (for example, JAVA_HOME\lib\security\cacerts).
Use '*' to signify to accept all certificates. Note that this is not recommended due to security concerns.
This section provides a complete list of schema properties you can configure.
| Property | Description |
| Location | A path to the directory that contains the schema files defining tables, views, and stored procedures. |
| BrowsableSchemas | This property restricts the schemas reported to a subset of the available schemas. For example, BrowsableSchemas=SchemaA, SchemaB, SchemaC. |
| Tables | This property restricts the tables reported to a subset of the available tables. For example, Tables=TableA, TableB, TableC. |
| Views | Restricts the views reported to a subset of the available tables. For example, Views=ViewA, ViewB, ViewC. |
| Dataverse | Which Analytics dataverse to scan when discovering tables. |
| TypeDetectionScheme | Determines how the provider builds tables and columns from the buckets found in Couchbase. |
| InferNumSampleValues | The maximum number of values for every field to scan before determining its data type. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER. |
| InferSampleSize | The maximum number of documents to scan for the columns available in the bucket. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER. |
| InferSimilarityMetric | Specifies the similarity degree where different schemas will be considered to be the same flavor. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER. |
| FlexibleSchemas | Whether the provider allows queries to use columns that it has not discovered. |
| ExposeTTL | Specifies whether document TTL information should be exposed. |
| NumericStrings | Whether to allow string values to be treated as numbers. |
| IgnoreChildAggregates | Whether the provider exposes aggregate columns that are also available as child tables. Ignored if TableSupport is not set to Full. |
| TableSupport | How much effort the provider will put into discovering tables on the Couchbase server. |
| NewChildJoinsMode | Determines the kind of child table model the provider exposes. |
A path to the directory that contains the schema files defining tables, views, and stored procedures.
string
"%APPDATA%\\Couchbase Data Provider\Schema"
The path to a directory which contains the schema files for the connector (.rsd files for tables and views, .rsb files for stored procedures). The folder location can be a relative path from the location of the executable. The Location property is only needed if you want to customize definitions (for example, change a column name, ignore a column, and so on) or extend the data model with new tables, views, or stored procedures.
If left unspecified, the default location is "%APPDATA%\\Couchbase Data Provider\Schema" with %APPDATA% being set to the user's configuration directory:
| Platform | %APPDATA% |
| Windows | The value of the APPDATA environment variable |
| Mac | ~/Library/Application Support |
| Linux | ~/.config |
This property restricts the schemas reported to a subset of the available schemas. For example, BrowsableSchemas=SchemaA,SchemaB,SchemaC.
string
""
Listing the schemas from databases can be expensive. Providing a list of schemas in the connection string improves the performance.
This property restricts the tables reported to a subset of the available tables. For example, Tables=TableA,TableB,TableC.
string
""
Listing the tables from some databases can be expensive. Providing a list of tables in the connection string improves the performance of the connector.
This property can also be used as an alternative to automatically listing views if you already know which ones you want to work with and there would otherwise be too many to work with.
Specify the tables you want in a comma-separated list. Each table should be a valid SQL identifier with any special characters escaped using square brackets, double-quotes or backticks. For example, Tables=TableA,[TableB/WithSlash],WithCatalog.WithSchema.`TableC With Space`.Note that when connecting to a data source with multiple schemas or catalogs, you will need to provide the fully qualified name of the table in this property, as in the last example here, to avoid ambiguity between tables that exist in multiple catalogs or schemas.
Restricts the views reported to a subset of the available tables. For example, Views=ViewA,ViewB,ViewC.
string
""
Listing the views from some databases can be expensive. Providing a list of views in the connection string improves the performance of the connector.
This property can also be used as an alternative to automatically listing views if you already know which ones you want to work with and there would otherwise be too many to work with.
Specify the views you want in a comma-separated list. Each view should be a valid SQL identifier with any special characters escaped using square brackets, double-quotes or backticks. For example, Views=ViewA,[ViewB/WithSlash],WithCatalog.WithSchema.`ViewC With Space`.
Note that when connecting to a data source with multiple schemas or catalogs, you will need to provide the fully qualified name of the table in this property, as in the last example here, to avoid ambiguity between tables that exist in multiple catalogs or schemas.
Which Analytics dataverse to scan when discovering tables.
string
""
This property is empty by default, which means that all dataverses will be scanned and table names will be generated as described in DataverseSeparator.
If you assign this property to a non-blank value, then the connector will scan only the corresponding dataverse (for example, setting this to "Default" scans the Default dataverse). Since only one dataverse is being scanned, table names will not be prefixed with the dataverse name. It is recommended to set this property to "Default" if you are coming from a previous version of the connector and need backwards compatability.
If you are connecting to Couchbase 7.0 or later, this option will be treated as a compound name containing both a dataset and a scope. For example, if you have previously created collections like these:
CREATE ANALYTICS SCOPE websites.exampledotcom CREATE ANALYTICS COLLECTION websites.exampledotcom.traffic ON examplecom_traffic_bucket CREATE ANALYTICS COLLECTION websites.exampledotcom.ads ON examplecom_ads_bucketYou would set this option to "websites.exampledotcom".
Determines how the provider builds tables and columns from the buckets found in Couchbase.
string
"DocType"
A comma-separated list of the following options:
| DocType | This discovers tables by checking at each bucket and looking for different values of the "docType" field in the documents. For example, if the bucket beer-sample contains documents with "docType" = 'brewery' and "docType" = 'beer', this will generate three tables: beer-sample (containing all documents), beer-sample.brewery (containing just breweries) and beer-sample.beer (containing just beers).
Like RowScan, this will scan a sample of the documents in each flavor and determine the data type for each field. RowScanDepth determines how many documents are scanned from each flavor. |
| DocType=fieldName | Like DocType, but this scans based off of a field called "fieldName" rather than "docType". "fieldName" must match the field name in Couchbase exactly, including case. |
| Infer | This uses the N1QL INFER statement to determine what tables and columns exist. This does more flexible flavor detection than DocType, but is only available for Couchbase Enterprise. |
| RowScan | This reads a sample of documents from a bucket, and heuristically determines the data type. RowScanDepth determines how many documents are scanned. It does not do any flavor detection. |
| None | This is like RowScan, but will always return columns that have string types instead of the detected type. |
The maximum number of values for every field to scan before determining its data type. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER.
string
"10"
The maximum number of values to scan from every field of the sampled documents before determining the field's data type. This property enables additional configuration of Automatic Schema Discovery when you are using the Couchbase Infer command -- TypeDetectionScheme must also be set to Infer to use this propery.
The maximum number of documents to scan for the columns available in the bucket. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER.
string
"100"
The maximum number of documents to scan for the columns available in the bucket. The Infer command will return column metadata by scanning a random sample of documents of the size specified here.
Setting a high value may decrease performance. Setting a low value may prevent the column and data type from being determined properly, especially when there is null data.
This property enables additional configuration of Automatic Schema Discovery when you are using the Couchbase Infer command -- TypeDetectionScheme must also be set to Infer to use this propery.Specifies the similarity degree where different schemas will be considered to be the same flavor. Applies to Automatic Schema Discovery when TypeDetectionScheme is set to INFER.
string
"0.7"
This property specifies how similar two schemas must be to be considered to be the same flavor. As an example, consider the following rows:
Row 1: ColA, ColB, ColC, ColD
Row 2: ColA, ColB, ColE, ColF
Row 3: ColB, ColF, ColX, ColY
You can configure the columns returned for each flavor with different InferSimilarityMetric values, as in the following examples:
You can then query document flavors using dot notation, as in the following statement:
SELECT * FROM [Items.Technology]
This property enables additional configuration of Automatic Schema Discovery when you are using the Couchbase Infer command -- TypeDetectionScheme must also be set to Infer to use this propery.
Whether the provider allows queries to use columns that it has not discovered.
bool
false
By default connector will only allow queries to use columns that it has found during the metadata discovery process (see TypeDetectionScheme for details). This means that the connector has the full information for each column it presents, but it also means that fields set on only a few documents may not be exposed. Disabling this option means that the connector will allow you to write a query with any columns you want. If you use columns in a query that have not been discovered the connector will assume that they are simple strings.
For example, the connector uses column type information to automatically convert dates for comparision since Couchbase cannot natively compare dates directly. If the connector detects that datecol is a date field, it can apply the STR_TO_MILLIS conversion automatically:
/* SQL */
WHERE datecol < '2020-06-12';
/* N1QL */
WHERE STR_TO_MILLIS(datecol) < STR_TO_MILLIS('2020-06-12');
When using undiscovered columns the connector cannot make this type of conversion for you. You must apply any needed conversions manually to ensure that operations behave the way you want them to.
Specifies whether document TTL information should be exposed.
bool
false
By default the connector does not expose TTL values or consider document TTLs when performing DML operations. Enabling this option exposes TTL values in two ways:
Note that enabling this features requires that your server be version 6.5.1 or later and that your CouchbaseService is set to N1QL. If either of these is not the case the connector will not connect.
Whether to allow string values to be treated as numbers.
bool
true
By default this property is enabled and the connector will treat string values as numeric if they all the values it samples during schema detection are numeric. This can cause type errors later on if the field contains non-numeric values in other documents. If this property is disabled then numeric strings are left as strings although other string-based data types like timestamps will still be detected.
For example, the "code" field in the below bucket would be affected by this setting. By default it would be considered an integer but if this property were enabled it would be treated as a string.
{ "code": "123", "message": "Please restart your computer" }
{ "code": "456", "message": "Urgent update must be applied" }
Whether the provider exposes aggregate columns that are also available as child tables. Ignored if TableSupport is not set to Full.
bool
false
The connector will expose array fields within a bucket as a separate child table, such as in the Games_scores example described in Automatic Schema Discovery. By default the connector will also expose these array fields as JSON aggregates on the base table. For example, either of these queries would return information on game scores:
/* Return each score as an individual row */ SELECT value FROM Games_scores; /* Return all scores for each Game as a JSON string */ SELECT scores FROM Games;
Since these aggregates are exposed on the base table, they will be generated even when the information they contain is redundant. For example, when performing this join the scores aggregate on Games is populated as well as the value column on Games_scores. Internally this causes two copies of the scores data to be transferred from Couchbase.
/* Retrieves score data twice, once for Games.scores and once for Games_scores.value */ SELECT * FROM Games INNER JOIN Games_scores ON Games.[Document.Id] = Games_scores.[Document.Id]
This option can be used to prevent the aggregate field from being exposed when the same information is also available from a child table. In the games example, setting this option to true means that the Games table would only expose a primary key column. The only way to retrieve information about scores would be the child table, so score data would only be read once from Couchbase.
/* Only exposes Document.Id, not scores */ SELECT * FROM Games; /* Only retrieves score data once for Games_scores.value */ SELECT * FROM Games INNER JOIN Games_scores ON Games.[Document.Id] = Games_scores.[Document.Id]
Note that this option overrides FlattenArrays, since all data from flattened arrays is also avaialable as child tables. If this option is set then no array flattening is performed, even if FlattenArrays is set to a value over 0.
How much effort the provider will put into discovering tables on the Couchbase server.
string
"Full"
The available options are:
| Full | The connector will discover the available buckets, and look inside of each of those buckets for child tables. This provides the most flexible way to access nested data, but requires that each bucket on your server have primary indexes. |
| Basic | The connector will discover the available buckets, but will not look inside of them for child tables. This is recommended for cases where you either want to reduce the time that schema detection takes, or if your buckets do not have primary indexes. |
| None | The connector will only use the schema files found in the Location directory, and will not discover buckets on the server. This option should only be used after you have already created schema files. Using this option without schema files will result in no tables being available. |
Determines the kind of child table model the provider exposes.
string
"false"
By default the connector exposes a backwards-compatible data model that is not fully relational. In this mode non-child tables have a primary key called Document.Id, but child tables do not have a primary key. Instead they have a column called Document.Id which has the same value as the Document.Id of the parent row that contains the child row.
For example, a parent table invoices containing invoice records may look like this:
| Document.Id | customer |
| 1 | Adam |
| 2 | Beatrice |
| 3 | Charlie |
And its child invoices_lineitems containing line items may look like this:
| Document.Id | item |
| 1 | laptop |
| 1 | keyboard |
| 2 | stapler |
| 3 | whiteboard |
| 3 | markers |
This model has several limitations:
The NewChildJoins data model is fully relational. In this mode non-child tables have the same Document.Id as before, but child tables are extended to have both a foreign key and a primary key. The foreign key is called Document.Parent and it refers to the Document.Id of the row in the parent table that contains the child row. The primary key is called Document.Id and it contains a path which uniquely refers to that child row.
For example, the same tables as above would look like this in the NewChildJoins model. invoices would be the same:
| Document.Id | customer |
| 1 | Adam |
| 2 | Beatrice |
| 3 | Charlie |
However, invoices_lineitems would have both a primary and foreign key. The primary key contains the ID of the parent row as well as the child row's position in the parent.
| Document.Id | Document.Parent | item |
| 1$1 | 1 | laptop |
| 1$2 | 1 | keyboard |
| 2$1 | 2 | stapler |
| 3$1 | 3 | whiteboard |
| 3$2 | 3 | markers |
This fixes the limitations of the old data model:
This section provides a complete list of miscellaneous properties you can configure.
| Property | Description |
| AllowJSONParameters | Allows raw JSON to be used in parameters when QueryPassthrough is enabled. |
| ChildSeparator | The character or characters used to denote child tables. |
| CreateTableRamQuota | The default RAM quota, in megabytes, to use when inserting buckets via the CREATE TABLE syntax. |
| DataverseSeparator | The character or characters used to denote Analytics dataverses and scopes/collections. |
| FlattenArrays | The number of elements to expose as columns from nested arrays. Ignored if IgnoreChildAggregates is enabled. |
| FlattenObjects | Set FlattenObjects to true to flatten object properties into columns of their own. Otherwise, objects nested in arrays are returned as strings of JSON. |
| FlavorSeparator | The character or characters used to denote flavors. |
| GenerateSchemaFiles | Indicates the user preference as to when schemas should be generated and saved. |
| InsertNullValues | Determines whether an INSERT should include fields that have NULL values. |
| MaxRows | Limits the number of rows returned rows when no aggregation or group by is used in the query. This helps avoid performance issues at design time. |
| Other | These hidden properties are used only in specific use cases. |
| Pagesize | The maximum number of results to return per page from Couchbase. |
| PeriodsSeparator | The character or characters used to denote hierarchy. |
| PseudoColumns | This property indicates whether or not to include pseudo columns as columns to the table. |
| QueryExecutionTimeout | This sets the server-side timeout for the query, which governs how long Couchbase will execute the query before returning a timeout error. |
| QueryPassthrough | This option passes the query to the Couchbase server as is. |
| RowScanDepth | The maximum number of rows to scan to look for the columns available in a table. |
| StrictComparison | Adjusts how precisely to translate filters on SQL input queries into Couchbase queries. This can be set to a comma-separated list of values, where each value can be one of: date, number, boolean, or string. |
| Timeout | The value in seconds until the timeout error is thrown, canceling the operation. |
| TransactionDurability | Specifies how a document must be stored for a transaction to succeed. Specifies whether to use N1QL transactions when executing queries. |
| TransactionTimeout | This sets the amount of time a transaction may execute before it is timed out by Couchbase. |
| UpdateNullValues | Determines whether an UPDATE writes NULL values as NULL, or removes them. |
| UseCollectionsForDDL | Whether to assume that CREATE TABLE statements use collections instead of flavors. Only takes effect when connecting to Couchbase v7+ and GenerateSchemaFiles is set to OnCreate. |
| UseTransactions | Specifies whether to use N1QL transactions when executing queries. |
| ValidateJSONParameters | Allows the provider to validate that string parameters are valid JSON before sending the query to Couchbase. |
Allows raw JSON to be used in parameters when QueryPassthrough is enabled.
bool
false
This option affects how string parameters are handled when using direct N1QL and SQL++ queries through QueryPassthrough. For example, consider this query:
INSERT INTO `bucket` (KEY, VALUE) VALUES ("1", @x)
By default, this option is disabled and string parameters are quoted and escaped into JSON strings. That means that any value can be safely used as a string parameter, but it also means that parameters cannot be used as raw JSON documents:
/*
* If @x is set to: test value " contains quote
*
* Result is a valid query
*/
INSERT INTO `bucket` (KEY, VALUE) VALUES ("1", "test value \" contains quote")
/*
* If @x is set to: {"a": ["valid", "JSON", "value"]}
*
* Result contains string instead of JSON document
*/
INSERT INTO `bucket` (KEY, VALUE) VALUES ("1", "{\"a\": [\"valid\", \"JSON\", \"value\"]})
When this option is enabled, string parameters are assumed to be valid JSON. This means that raw JSON documents can be used as parameters, but it also means that all simple strings must be escaped:
/*
* If @x is set to: test value " contains quote
*
* Result is an invalid query
*/
INSERT INTO `bucket` (KEY, VALUE) VALUES ("1", test value " contains quote)
/*
* If @x is set to: {"a": ["valid", "JSON", "value"]}
*
* Result is a JSON document
*/
INSERT INTO `bucket` (KEY, VALUE) VALUES ("1", {"a": ["valid", "JSON", "value"]})
Please refer to ValidateJSONParameters for more details on how parameters are validated when this option is enabled.
The character or characters used to denote child tables.
string
"_"
When creating a child table for an array underneath a bucket, the connector will generate the name of the child table by concatenating the name of the base table, along with this separator and each path element.
For example, if this document were in the bucket "customers", then the child table for the addresses field would be called "customers_addresses".
{
"addresses": [
{"street": "123 Main St"},
{"street": "424 Pleasant Ct"},
{"street": "719 Blue Way"}
]
}
The default RAM quota, in megabytes, to use when inserting buckets via the CREATE TABLE syntax.
string
"250"
The default RAM quota, in megabytes, to use when inserting buckets via the CREATE TABLE syntax.
The character or characters used to denote Analytics dataverses and scopes/collections.
string
"."
When using the Analytics serivce, the connector will scan all datasets from all available dataverses. To avoid potential name conflicts, it will include the dataverse name and the dataset name in the generated table name.
By default this is set to ".", so that if there is a dataset called "users" on the "Default" dataverse, then the table generated will be "Default.users".
This property is also used when generating table names for collections (on both N1QL and Analytics) on Couchbase 7 and later. For example, a bucket called "users" that has two collections called "active" and "inactive" under the "status" scope would be detected as the tables "users.status.active" and "users.status.inactive".
The number of elements to expose as columns from nested arrays. Ignored if IgnoreChildAggregates is enabled.
string
"0"
By default, nested arrays are returned as strings of JSON. The FlattenArrays property can be used to flatten the elements of nested arrays into columns of their own. This is only recommended for arrays that are expected to be short.
Set FlattenArrays to the number of elements you want to return from nested arrays. The specified elements are returned as columns. The zero-based index is concatenated to the column name. Other elements are ignored.
For example, you can return an arbitrary number of elements from an array of strings:
["FLOW-MATIC","LISP","COBOL"]When FlattenArrays is set to 1, the preceding array is flattened into the following table:
| Column Name | Column Value |
| languages.0 | FLOW-MATIC |
Set FlattenObjects to true to flatten object properties into columns of their own. Otherwise, objects nested in arrays are returned as strings of JSON.
bool
true
Set FlattenObjects to true to flatten object properties into columns of their own. Otherwise, objects nested in arrays are returned as strings of JSON. The property name is concatenated onto the object name with an underscore to generate the column name.
For example, you can flatten the nested objects below at connection time:
address : {
"street" : "123 Main St.",
"city" : "Nowhere",
"state" : "NY",
"zip" : "12345"
}
When FlattenObjects is set to true, the preceding object is flattened into the following table:
| Column Name | Column Value |
| address.street | 123 Main St. |
| address.city | Nowhere |
| address.state | NY |
| address.zip | 12345 |
The character or characters used to denote flavors.
string
"."
When the connector detects a flavored table, using either a DocType or Infer TypeDetectionScheme, it names flavored tables by concatenating the underlying bucket name, this seprator, and the value of the bucket's primary flavor.
For example, if the connector detects the flavor "docType = 'beer'" on the "beer-sample" bucket, then it will generate the table "beer-sample.beer" which contains only documents in "beer-sample" which have the "beer" doctype.
Indicates the user preference as to when schemas should be generated and saved.
string
"Never"
GenerateSchemaFiles enables you to save the table definitions identified by Automatic Schema Discovery. This property outputs schemas to .rsd files in the path specified by Location.
Available settings are the following:
Note that if you want to regenerate a file, you will first need to delete it.
When you set GenerateSchemaFiles to OnUse, the connector generates schemas as you execute SELECT queries. Schemas are generated for each table referenced in the query.
When you set GenerateSchemaFiles to OnCreate, schemas are only generated when a CREATE TABLE query is executed.
Another way to use this property is to obtain schemas for every table in your database when you connect. To do so, set GenerateSchemaFiles to OnStart and connect.
If your data structures are volatile, consider setting GenerateSchemaFiles to Never and using dynamic schemas. See Automatic Schema Discovery for more information about dynamic schemas.
Schema files have a simple format that makes them easy to modify. See Custom Schema Definitions for more information.
Determines whether an INSERT should include fields that have NULL values.
bool
true
By default the connector uses NULL values provided in an INSERT statement and inserts them as JSON null values.
If this option is disabled, SQL NULL values are ignored during an INSERT. In the case of array columns (FlattenArrays must be set to retrieve these), this means that array indices are shifted over to compensate for the values that have been removed.
Limits the number of rows returned rows when no aggregation or group by is used in the query. This helps avoid performance issues at design time.
int
-1
Limits the number of rows returned rows when no aggregation or group by is used in the query. This helps avoid performance issues at design time.
These hidden properties are used only in specific use cases.
string
""
The properties listed below are available for specific use cases. Normal driver use cases and functionality should not require these properties.
Specify multiple properties in a semicolon-separated list.
| DefaultColumnSize | Sets the default length of string fields when the data source does not provide column length in the metadata. The default value is 2000. |
| ConvertDateTimeToGMT | Determines whether to convert date-time values to GMT, instead of the local time of the machine. |
| RecordToFile=filename | Records the underlying socket data transfer to the specified file. |
The maximum number of results to return per page from Couchbase.
int
1000
The Pagesize property affects the maximum number of results to return per page from Couchbase. Setting a higher value may result in better performance at the cost of additional memory allocated per page consumed.
The character or characters used to denote hierarchy.
string
"."
When flattening objects and arrays, the connector will use this value to separate different levels of objects and arrays. For example, if your Couchbase server returns a document like this (and FlattenObjects is enabled), then the connector will return the columns "geo.latitude" and "geo.longitude" if the periods separator is set to ".".
{
"geo": {
"latitude": 35.9132,
"longitude": -79.0558
}
}
This property indicates whether or not to include pseudo columns as columns to the table.
string
""
This setting is particularly helpful in Entity Framework, which does not allow you to set a value for a pseudo column unless it is a table column. The value of this connection setting is of the format "Table1=Column1, Table1=Column2, Table2=Column3". You can use the "*" character to include all tables and all columns; for example, "*=*".
This sets the server-side timeout for the query, which governs how long Couchbase will execute the query before returning a timeout error.
string
"-1"
Th default is -1, which disables the timeout. When enabling the timeout, the value must include both an amount and a unit, which can be one of: "ns" (nanoseconds), "us" (microseconds), "ms" (milliseconds), "s" (seconds), "m" (minutes) or "h" (hours). For example, "5m" and "300s" both set timeouts of 5 minutes.
There is a server-side timeout as well called the "index scan timeout", which will override this one if it is lower. By default the index scan timeout is 2 minutes, but it can be changed by setting the "indexer.settings.scan_timeout" property on your Couchbase server.
This option passes the query to the Couchbase server as is.
bool
false
When this is set, queries are passed through directly to Couchbase.
The maximum number of rows to scan to look for the columns available in a table.
int
100
The columns in a table must be determined by scanning table rows. This value determines the maximum number of rows that will be scanned.
Setting a high value may decrease performance. Setting a low value may prevent the data type from being determined properly, especially when there is null data.Adjusts how precisely to translate filters on SQL input queries into Couchbase queries. This can be set to a comma-separated list of values, where each value can be one of: date, number, boolean, or string.
string
""
This option is empty by default, which means that WHERE clauses sent to Couchbase will include extra functions that convert values so that more comparisons work.
For example, leaving the "string" setting out of the list causes arrays to be converted, so that they can be compared with strings:
SELECT * FROM Bucket WHERE MyArrayColumn = '[1,2,3]'
If set to a value, queries including the relevant types of comparisons will be translated literally. This makes better use of Couchbase's indexes, but means that the types of comparisons must be in a format Couchbase can compare directly.
For example, if "date" is provided as one of the options, then dates must match the format they are stored as in Couchbase since they will not be converted automatically:
SELECT * FROM Bucket WHERE MyDateColumn = '2018-10-31T10:00:00';
The value in seconds until the timeout error is thrown, canceling the operation.
int
60
If Timeout = 0, operations do not time out. The operations run until they complete successfully or until they encounter an error condition.
If Timeout expires and the operation is not yet complete, the connector throws an exception.
Specifies how a document must be stored for a transaction to succeed. Specifies whether to use N1QL transactions when executing queries.
string
"Majority"
If UseTransactions is enabled, then this option can be set to determine when Couchbase will allow writes in transactions to commit. The Couchbase documentation on Durability and Transactions contains the full details, below is a high-level summary.
This option controls requirements on both quorum and persistence. The quorum may either require no bucket replicas to receive the document (None), or a majority of replicas to have the document (all others). The persistence level requires either that the document be stored in the replica memory (Majoriy) or on the replica disk (MajorityAndPersistActive, PersistToMajority).
None is only useful if the bucket you are using is not configured for replicas. The other options can be used depending on the required performance and durability tradeoffs. Persisting to more replicas is slower but provides greater resilience against a node crashing.
This sets the amount of time a transaction may execute before it is timed out by Couchbase.
string
""
If transactions are enabled, then the connector will default to the server's default transaction timeout setting.
When enabling the timeout, the value must include both an amount and a unit, which can be one of: "ns" (nanoseconds), "us" (microseconds), "ms" (milliseconds), "s" (seconds), "m" (minutes) or "h" (hours). For example, "5m" and "300s" both set timeouts of 5 minutes.
There are also cluster-level and node-level transaction timeouts which override this one if they are smaller. For example, if the node-level timeout is set to a minute then setting this option to "5m" will have no effect.
Determines whether an UPDATE writes NULL values as NULL, or removes them.
bool
true
By default the connector will use NULL values provided in an UPDATE statement and set the field in Couchbase to NULL.
If this option is disabled SQL NULL values in an UPDATE will cause the connector to mark the field as MISSING. This removes the field from the object containing it, or if the field is contained in an array (per FlattenArrays) then that element is set to NULL.
This option should be used with care as the connector may not detect that the field exists if it is removed from enough documents within a bucket.
Whether to assume that CREATE TABLE statements use collections instead of flavors. Only takes effect when connecting to Couchbase v7+ and GenerateSchemaFiles is set to OnCreate.
bool
false
Normally the connector will assume that compound table names referenced in a CREATE TABLE statement are flavors. For compatibility, this is still the default with Couchbase v7+ even though flavors are not recommended there.
CREATE TABLE [myBucket.myFlavor]( [Document.Id] VARCHAR PRIMARY KEY, docType VARCHAR, sometext VARCHAR, somenum INT )
Enable this option to assume that CREATE TABLE statements refer to collection instead. In that scenario this query willl create the bucket and scope if necessary, before creating the colleciton and setting a primary index:
CREATE TABLE [myBucket.myScope.myCollection]( [Document.Id] VARCHAR PRIMARY KEY, sometext VARCHAR, somenum INT )
Specifies whether to use N1QL transactions when executing queries.
string
"Never"
By default the connector does not use transactions for compatibility with older versions of Couchbase. All of the other options require a connection to Couchbase 7 or above. The N1QL service must also be enabled using CouchbaseService.
Setting this to Always means that all queries will use transactions. An explicit transaction may be created on the connection and queries will use that transaction while it is active. If there is no explicit transaction then queries will use implicit transactions instead.
Setting this to Explicit enables support for explicit transactions only. Explicit transactions may be created but if one is not currently active, then statements will not create an implicit transaction.
Allows the provider to validate that string parameters are valid JSON before sending the query to Couchbase.
bool
true
When AllowJSONParameters and QueryPassthrough are enabled, the query parameters given to the connector will be treated as raw JSON documents instead of arbitrary string values. This option controls what happens when invalid JSON is given to the connector in this mode.
When this option is enabled, the connector will check that all string parameters can be parsed as valid JSON. If any cannot be, an error will be raised and the query will not be run.
When this option is disabled, no check is performed and all string parameter values are substituted into the query directly. This makes executing prepared statements faster, but less safe since invalid N1QL or SQL++ may be sent to the Couchbase.