Apache CouchDB Connection Details

Introduction

Connector Version

This documentation is based on version 23.0.9039 of the connector.

Get Started

Apache CouchDB Version Support

The connector supports CouchDB version 1.6 and above. See Query Mapping for SQL-to-ApacheCouchDB-query mappings and more information about accessing unstructured data in Apache CouchDB through SQL.

Establish a Connection

Connect to Apache CouchDB

Apache CouchDB supports three types of authentication:

• Basic: Basic username/password authentication.
• JWT: Authentication with JWT token.
• None: Anonymous access for databases that are public.

If you want your users (or JWT tokens) to have access to only specific databases, you have to configure the admin_only_all_dbs option in the Apache CouchDB instance to grant all users access to the "/_all_dbs" endpoint which is required by the connector for listing tables. Otherwise the connector won't be able to connect, because the endpoint will throw an authentication error.

Basic Authentication

Set the following to connect to data:

• AuthScheme: Basic.
• URL: The Url of your Apache CouchDB instance. For example: http://localhost:5984
• User The Apache CouchDB user account used to authenticate.
• Password The Apache CouchDB password associated with the authenticating user.

JWT Authentication

The following connection properties are required and must always be specified:

• AuthScheme: JWT.
• URL: The Url of your Apache CouchDB instance. For example: http://localhost:5984.

From here you can:

1. Set the following so that the connector automatically generates (and refreshes if applicable) the tokens for you:

Required

• JWTSubject: The name of the user to assign to the JWT token.
• JWTAlgorithm: The algorithm to use for the JWT token signature.
• JWTKeyType: The type of the encryption key.
• JWTKey: The encryption key used to sign the JWT token generated by the connector.

Optional

• JWTIssuer: The issuer of the JWT token.
• JWTExpiration: How long the JWT token should remain valid, in seconds.
• JWTHeaders: A collection of extra headers that should be included in the JWT header.
• JWTClaims: A collection of extra claims that should be included in the JWT payload.
• CredentialsLocation: The location of the settings file where the JWT token is saved.

2. Or you can generate the tokens yourself manually and pass them to the connector by using the JWTToken connection property.

Generate the key pair

When using asymmetric algorithms to sign the tokens, you must generate a private/public key pair. For that, a cryptographic library like OpenSSL can be used. For example:

# generate private key
openssl genrsa --out private_rsa256.pem 2048

# extract public key
openssl rsa -in private_rsa256.pem -pubout > public_rsa256.pem

JWT Configurations

Refer to CouchDB JWT Authentication Documentation for the following.

The alg and sub are required claims and will always be validated by the Apache CouchDB instance. Other required claims can be configured in the server (see required_claims). In that case, you must use JWTHeaders and JWTClaims so that the connector can include those additional claims when generating the JWT token.

You can use roles_claim_name or the roles_claim_path options to assign roles to the JWT tokens.

Refer to the following example for configuring the server and the connector:

server configuration

[chttpd]
...
authentication_handlers = {chttpd_auth, jwt_authentication_handler}, {chttpd_auth, cookie_authentication_handler}, {chttpd_auth, default_authentication_handler}
admin_only_all_dbs = false
...

[jwt_auth]
...
required_claims = exp
roles_claim_path = my.nested._couchdb\.roles
rsa:rsa_256 = -----BEGIN PUBLIC KEY-----\nYOUR_PUBLIC_KEY\n-----END PUBLIC KEY-----\n

...

connector configuration

Url=http://localhost:5984;
JWTSubject=JWT User 1;
JWTAlgorithm=RS256;
JWTKeyType=PEMKEY_FILE;
JWTKey=PATH_TO_FOLDER\private_rsa256.pem;
JWTHeaders=kid : rsa_256 | Custom Header 1 : Test 1;

JWTClaims= my : eyJuZXN0ZWQiOnsiX2NvdWNoZGIucm9sZXMiOlsidXNlcjIiXX19 | Custom Claim 1 : Test 1;

Anonymous

Set the following to connect to data:

• AuthScheme: None.
• URL: The Url of your Apache CouchDB instance. For example: http://localhost:5984
• PublicDatabases: A comma-separated list of public databases to list as tables.

Fine-Tuning Data Access

Infer the Data Type

You can use the following properties to configure automatic data type detection, which is enabled by default.

• TypeDetectionScheme: You can use this property to enable or disable automatic type detection based on the value specified in RowScanDepth.
• RowScanDepth: This property determines the number of rows that will be scanned to determine column data types.

Important Notes

Configuration Files and Their Paths

• All references to adding configuration files and their paths refer to files and locations on the Jitterbit agent where the connector is installed. These paths are to be adjusted as appropriate depending on the agent and the operating system. If multiple agents are used in an agent group, identical files will be required on each agent.

NoSQL Database

Apache CouchDB is a schema-less 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 following sections show various schemes that the connector offers to bridge the gap with relational SQL and a document database.

Automatic Schema Discovery

The Automatic Schema Discovery scheme automatically finds the data types in an Apache CouchDB object by scanning a configured number of rows of the object. You can use RowScanDepth, FlattenArrays, and FlattenObjects to control the relational representation of the collections in Apache CouchDB.

Parse Nested Data

The connector models the schemaless Apache CouchDB objects into relational tables and translates SQL queries into Apache CouchDB queries to get the requested data.

Free-Form Queries

The schema of the table is necessary to report metadata, but you can write Free-Form Queries not tied to the schema to select, insert, update, or delete data from columns that do not exist in the schema (without flattening).

Vertical Flattening

See Vertical Flattening to process JSON arrays as separate tables.

JSON Functions

See JSON Functions for query examples that can access specific nested data manually.

Query Mapping

See Query Mapping for more details on how various Apache CouchDB operations are represented as SQL.

Dynamic Views

The connector supports listing Apache CouchDB views and retrieving data from them. This is controlled by the ListViews property, which is set to false by default. Set this property to true for Apache CouchDB views to be displayed when listing tables.

Automatic Schema Discovery

The connector automatically infers a relational schema by inspecting a series of Apache CouchDB documents in a collection. You can use the RowScanDepth property to define the number of documents the connector will scan to do so. The columns identified during the discovery process depend on the FlattenArrays and FlattenObjects properties.

Flatten Objects

If FlattenObjects is set, all nested objects will be flattened into a series of columns. For example, consider the following document:

{
  id: 12,
  name: "Lohia Manufacturers Inc.",
  address: {street: "Main Street", city: "Chapel Hill", state: "NC"},
  offices: ["Chapel Hill", "London", "New York"],
  annual_revenue: 35,600,000
}

This document will be represented by the following columns:

If FlattenObjects is not set, then the address.street, address.city, and address.state columns will not be broken apart. The address column of type string will instead represent the entire object. Its value would be {street: "Main Street", city: "Chapel Hill", state: "NC"}. See JSON Functions for more details on working with JSON aggregates. You can change the separator character in the column name from a dot by setting SeparatorCharacter.

Flatten Arrays

The FlattenArrays property can be used to flatten array values into columns of their own. This is only recommended for arrays that are expected to be short, for example the coordinates below:

"coord": [ -73.856077, 40.848447 ]

The FlattenArrays property can be set to 2 to represent the array above as follows:

It is best to leave other unbounded arrays as they are and piece out the data for them as needed using JSON Functions.

Free-Form Queries

As discussed in Automatic Schema Discovery, intuited table schemas enable SQL access to unstructured Apache CouchDB data. JSON Functions enable you to use standard JSON functions to summarize Apache CouchDB data and extract values from any nested structures. However, you are not limited to these schemes.

After connecting you can query any nested structure without flattening the data. Any relations that you can access with FlattenArrays and FlattenObjects can also be accessed with an ad hoc SQL query.

Let's consider an example document from the following Restaurant data set:

{
  "address": {
    "building": "1007",
    "coord": [
      -73.856077,
      40.848447
    ],
    "street": "Morris Park Ave",
    "zipcode": "10462"
  },
  "borough": "Bronx",
  "cuisine": "Bakery",
  "grades": [
    {
      "grade": "A",
      "score": 2,
      "date": {
        "$date": "1393804800000"
      }
    },
    {
      "date": {
        "$date": "1378857600000"
      },
      "grade": "B",
      "score": 6
    },
    {
      "score": 10,
      "date": {
        "$date": "1358985600000"
      },
      "grade": "C"
    }
  ],
  "name": "Morris Park Bake Shop",
  "restaurant_id": "30075445"
} 

You can access any nested structure in this document as a column. Use the dot notation to drill down to the values you want to access as shown in the query below. Note that arrays have a zero-based index. For example, the following query retrieves the second grade for the restaurant in the example:

SELECT [address.building], [grades.1.grade] FROM restaurants WHERE restaurant_id = '30075445'

The preceding query returns the following results:

Vertical Flattening

It is possible to retrieve an array of documents as if it were a separate table. Take the following JSON structure from the restaurants collection for example:

{
  "_id" : ObjectId("568c37b748ddf53c5ed98932"),
  "address" : {
    "building" : "1007",
    "coord" : [-73.856077, 40.848447],
    "street" : "Morris Park Ave",
    "zipcode" : "10462"
  },
  "borough" : "Bronx",
  "cuisine" : "Bakery",
  "grades" : [{
      "date" : ISODate("2014-03-03T00:00:00Z"),
      "grade" : "A",
      "score" : 2
    }, {
      "date" : ISODate("2013-09-11T00:00:00Z"),
      "grade" : "A",
      "score" : 6
    }, {
      "date" : ISODate("2013-01-24T00:00:00Z"),
      "grade" : "A",
      "score" : 10
    }, {
      "date" : ISODate("2011-11-23T00:00:00Z"),
      "grade" : "A",
      "score" : 9
    }, {
      "date" : ISODate("2011-03-10T00:00:00Z"),
      "grade" : "B",
      "score" : 14
    }],
  "name" : "Morris Park Bake Shop",
  "restaurant_id" : "30075445"
}

Vertical flattening will allow you to retrieve the grades array as a separate table:

SELECT * FROM [restaurants.grades]

This query returns the following data set:

You may also want to include information from the base restaurants table. You can do this with a join. Flattened arrays can only be joined with the root document. The connector expects the left part of the join is the array document you want to flatten vertically. Disable SupportEnhancedSQL to join nested Apache CouchDB documents -- this type of query is supported through the Apache CouchDB API.

SELECT [restaurants].[restaurant_id], [restaurants.grades].* FROM [restaurants.grades] JOIN [restaurants] WHERE [restaurants].name = 'Morris Park Bake Shop'

This query returns the following data set:

JSON Functions

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 }
]

JSON_EXTRACT

The JSON_EXTRACT function can extract individual values from a JSON object. The following query returns the values shown below based on the JSON path passed as the second argument to the function:

SELECT Name, JSON_EXTRACT(grades,'[0].grade') AS Grade, JSON_EXTRACT(grades,'[0].score') AS Score FROM Students;

JSON_COUNT

The JSON_COUNT function returns the number of elements in a JSON array within a JSON object. The following query returns the number of elements specified by the JSON path passed as the second argument to the function:

SELECT Name, JSON_COUNT(grades,'[x]') AS NumberOfGrades FROM Students;

JSON_SUM

The JSON_SUM function returns the sum of the numeric values of a JSON array within a JSON object. The following query returns the total of the values specified by the JSON path passed as the second argument to the function:

SELECT Name, JSON_SUM(score,'[x].score') AS TotalScore FROM Students;

JSON_MIN

The JSON_MIN function returns the lowest numeric value of a JSON array within a JSON object. The following query returns the minimum value specified by the JSON path passed as the second argument to the function:

SELECT Name, JSON_MIN(score,'[x].score') AS LowestScore FROM Students;

JSON_MAX

The JSON_MAX function returns the highest numeric value of a JSON array within a JSON object. The following query returns the maximum value specified by the JSON path passed as the second argument to the function:

SELECT Name, JSON_MAX(score,'[x].score') AS HighestScore FROM Students;

DOCUMENT

The DOCUMENT function can be used to retrieve the entire document as a JSON string. See the following query and its result as an example:

SELECT DOCUMENT(*) FROM Customers;

The query above will return the entire document as shown.

{ "id": 12, "name": "Lohia Manufacturers Inc.", "address": { "street": "Main Street", "city": "Chapel Hill", "state": "NC"}, "offices": [ "Chapel Hill", "London", "New York" ], "annual_revenue": 35,600,000 }

Query Mapping

The connector maps SQL queries into the corresponding Apache CouchDB queries. The connector uses the Selector syntax to compute the desired results.

A detailed description of all the transformations is out of scope, but we will describe some of the common elements that are used.

SELECT Queries

The SELECT statement is mapped to the GET and POST methods. Below are example queries and the corresponding request payloads.

SELECT *
FROM sales

SELECT _id, value
FROM sales

{
"fields": [
"_id",
"value"
],
"skip": 0,
"selector": {
"_id": {
"$exists": true
}
}
}

SELECT *
FROM sales
WHERE value=175033291697

{
"selector": {
"value": {
"$eq": 175033291697
}
},
"skip": 0
}

SELECT *
FROM sales
WHERE value = 175033291697 OR month='June'

{
"selector": {
"$or": [
{
"value": {
"$eq": 175033291697
}
},
{
"month": {
"$eq": "June"
}
}
]
},
"skip": 0
}

SELECT *
FROM sales
WHERE name LIKE 'A%'

{
"selector": {
"name": {
"$regex": "A%"
}
},
"skip": 0
}

SELECT * FROM sales
WHERE month='June'
ORDER BY _id ASC

{
"skip": 0,
"sort": [
{
"_id": "asc"
}
],
"selector": {
"month": {
"$eq": "June"
}
}
}

SELECT *
FROM sales
WHERE month='June'
ORDER BY _id DESC

{
"skip": 0,
"sort": [
{
"_id": "desc"
}
],
"selector": {
"month": {
"$eq": "June"
}
}
}

INSERT Statements

The INSERT statement is mapped to the HTTP POST request, as shown in the following query and request payload.

SQL Query

INSERT INTO users (_id, age, status, [address.city], [address.postalcode])

VALUES ('bcd001', 45, 'A', 'Chapel Hill', 27517)

Apache CouchDB Query

{
  "address": {
    "city": "Chapel Hill",
    "postalcode": 27517
  },
  "_id": "bcd001",
  "age": 45,
  "status": "A"

}

UPDATE Statements

The UPDATE statement is mapped to the HTTP PUT method, as shown in the following query and request payload.

SQL Query

UPDATE users
SET status = 'C', [address.postalcode] = 90210

WHERE _id = 'bcd001'

Apache CouchDB Query

{
  "_id": "bcd001",
  "_rev": "1-446f6c67e3a483feae8eaf112f18892c",
  "status": "C",
  "age": 45,
  "address": {
    "city": "Chapel Hill",
    "postalcode": 90210
  }

}

DELETE Statements

The DELETE statement is mapped to the DELETE method as shown below.

SQL Query

DELETE FROM users WHERE _id = 'bcd001'

Apache CouchDB Query

For this query, a DELETE request is sent to the users/{_id}?rev={_rev} endpoint.

System Tables

You can query the system tables described in this section to access schema information, information on data source functionality, and batch operation statistics.

Schema Tables

The following tables return database metadata for Apache CouchDB:

• sys_catalogs: Lists the available databases.
• sys_schemas: Lists the available schemas.
• sys_tables: Lists the available tables and views.
• sys_tablecolumns: Describes the columns of the available tables and views.
• sys_procedures: Describes the available stored procedures.
• sys_procedureparameters: Describes stored procedure parameters.
• sys_keycolumns: Describes the primary and foreign keys.
• sys_indexes: Describes the available indexes.

Data Source Tables

The following tables return information about how to connect to and query the data source:

• sys_connection_props: Returns information on the available connection properties.
• sys_sqlinfo: Describes the SELECT queries that the connector can offload to the data source.

Query Information Tables

The following table returns query statistics for data modification queries:

• sys_identity: Returns information about batch operations or single updates.

sys_catalogs

Lists the available databases.

The following query retrieves all databases determined by the connection string:

SELECT * FROM sys_catalogs

Columns

sys_schemas

Lists the available schemas.

The following query retrieves all available schemas:

SELECT * FROM sys_schemas

Columns

sys_tables

Lists the available tables.

The following query retrieves the available tables and views:

SELECT * FROM sys_tables

Columns

sys_tablecolumns

Describes the columns of the available tables and views.

The following query returns the columns and data types for the Movies table:

SELECT ColumnName, DataTypeName FROM sys_tablecolumns WHERE TableName='Movies'

Columns

sys_procedures

Lists the available stored procedures.

The following query retrieves the available stored procedures:

SELECT * FROM sys_procedures

Columns

sys_procedureparameters

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

Columns

sys_keycolumns

Describes the primary and foreign keys.

The following query retrieves the primary key for the Movies table:

SELECT * FROM sys_keycolumns WHERE IsKey='True' AND TableName='Movies'

Columns

sys_foreignkeys

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'

Columns

sys_primarykeys

Describes the primary keys.

The following query retrieves the primary keys from all tables and views:

SELECT * FROM sys_primarykeys

Columns

sys_indexes

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'

Columns

sys_connection_props

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:apachecouchdb: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 <> ''

Columns

sys_sqlinfo

Describes the SELECT query processing that the connector can offload to the data source.

Discover the Data Source's SELECT Capabilities

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.

The following query retrieves the operators that can be used in the WHERE clause:

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 NoSQL Database section for more information.

Columns

sys_identity

Returns information about attempted modifications.

The following query retrieves the Ids of the modified rows in a batch operation:

SELECT * FROM sys_identity

Columns

sys_information

Describes the available system information.

The following query retrieves all columns:

SELECT * FROM sys_information

Columns

Stored Procedures

Stored procedures are function-like interfaces that extend the functionality of the connector beyond simple SELECT/INSERT/UPDATE/DELETE operations with Apache CouchDB.

Stored procedures accept a list of parameters, perform their intended function, and then return any relevant response data from Apache CouchDB, along with an indication of whether the procedure succeeded or failed.

Apache CouchDB Connector Stored Procedures

CreateSchema

Creates a schema definition of a table in Apache CouchDB. Control column discovery with the connection properties FlattenObjects, FlattenArrays, TypeDetectionScheme, and RowScanDepth.

CreateSchema

Creates a local schema file (.rsd) from an existing table or view in the data model.

The schema file is created in the directory set in the Location connection property when this procedure is executed. You can edit the file to include or exclude columns, rename columns, or adjust column datatypes.

The connector checks the Location to determine if the names of any .rsd files match a table or view in the data model. If there is a duplicate, the schema file will take precedence over the default instance of this table in the data model. If a schema file is present in Location that does not match an existing table or view, a new table or view entry is added to the data model of the connector.

Input

Result Set Columns

Advanced Configurations Properties

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.

Authentication

JWT Authentication

SSL

Schema

Miscellaneous

Authentication

This section provides a complete list of authentication properties you can configure.

AuthScheme

The type of authentication to use when connecting to Apache CouchDB.

Possible Values

Basic, JWT, None

Data Type

string

Default Value

Basic

Remarks

• Basic: Set this to use basic User/Password authentication.
• JWT: JWT token authentication.
• None: No authentication is used.

URL

The URL used to connect to the Apache CouchDB.

Data Type

string

Default Value

""

Remarks

The URL used to connect to the Apache CouchDB in the format http://{server}:{port}.

User

The Apache CouchDB user account used to authenticate.

Data Type

string

Default Value

""

Remarks

Together with Password, this field is used to authenticate against the Apache CouchDB server.

Password

The password used to authenticate the user.

Data Type

string

Default Value

""

Remarks

The User and Password are together used to authenticate with the server.

PublicDatabases

Specify a comma-separated list of public databases to list as tables.

Data Type

string

Default Value

""

Remarks

This is needed for anonymous access (AuthScheme=None) because the database listing call requires user authentication.

JWT Authentication

This section provides a complete list of the JWT Authentication properties you can configure.

JWTToken

The JWT token to use for authentication.

Data Type

string

Default Value

""

Remarks

This connection property can be used in case you want to generate the token yourself and pass it directly here. In that case the connector will not generate the token itself, but use the token from the connection.

JWTSubject

The user subject for which the application is requesting delegated access.

Data Type

string

Default Value

""

Remarks

This is used as the sub claim in the JWT token.

Apache CouchDB uses this as the user’s name when validating the JWT token.

JWTIssuer

The issuer of the JWT token.

Data Type

string

Default Value

""

Remarks

The issuer of the JWT token. Although the default value is not documented above, this connection property does has a default value and that value simply contains information abut the connector. For example: "ApacheCouchDB JDBC v24".

JWTAlgorithm

The encryption algorithm used for signing the JWT token.

Possible Values

HS512, ES384, RS256, ES512, RS384, HS256, RS512, HS384, ES256

Data Type

string

Default Value

RS256

Remarks

This is used as the alg claim in the JWT token. This property can take one of the following values:

JWTExpiration

How long the JWT token should remain valid, in seconds.

Data Type

int

Default Value

-1

Remarks

This is used to calculate the exp claim in the JWT token. By default this is set to -1 which means the driver will never refresh after generating the first token.

JWTKeyType

The type of the encryption key which is used for signing the JWT token.

Possible Values

PEMKEY_FILE, PEMKEY_BLOB, SYMMETRIC

Data Type

string

Default Value

PEMKEY_FILE

Remarks

This property can take one of the following values:

JWTKey

The encryption key for signing the JWT token.

Data Type

string

Default Value

""

Remarks

The encryption key used for signing the JWT token generated by the connector. The JWTKeyType field specifies the type of the key being used.

JWTHeaders

A collection of extra headers that should be included in the JWT header.

Data Type

string

Default Value

""

Remarks

The string should not contain any single quotes or double quotes and `:** and **|` have to be used as delimiters. For example:

JWTHeaders = kid : key_1 | Custom Header 1 : value;

If you need to use more complex values such as JSON objects or arrays, they have to be base64 encoded. For example:

JWTHeaders = kid : key_1 | my : eyJjdXN0b20iOlsianNvbiIsIm9iamVjdCJdfQ==;

By default, not all the headers in the JWT token are validated by the Apache CouchDB (only alg). See the documentation of required_claims for enforcing the validation of additional headers. In that case, you can configure this connection property as well so that the connector includes them when generating the token.

JWTClaims

A collection of extra claims that should be included in the JWT payload.

Data Type

string

Default Value

""

Remarks

The string should not contain any single quotes or double quotes and `:** and **|` have to be used as delimiters. For example:

JWTClaims = aud : https://my.couchdb.server | nbf : 1720444762;

If you need to use more complex values such as JSON objects or arrays, they have to be base64 encoded. For example:

JWTClaims = my : eyJuZXN0ZWQiOnsiX2NvdWNoZGIucm9sZXMiOlsidXNlcjIiXX19 | nbf : 1720444762;

By default, not all the claims in the JWT token are validated by the Apache CouchDB (only sub). See the documentation of required_claims for enforcing the validation of additional claims. In that case, you can configure this connection property as well so that the connector includes them when generating the token.

CredentialsLocation

The location of the settings file where the JWT token is saved.

Data Type

string

Default Value

%APPDATA%\ApacheCouchDB Data Provider\CredentialsFile.txt

Remarks

If left unspecified, the default location is "%APPDATA%\ApacheCouchDB Data Provider\CredentialsFile.txt" with %APPDATA% being set to the user's configuration directory:

SSL

This section provides a complete list of SSL properties you can configure.

SSLServerCert

The certificate to be accepted from the server when connecting using TLS/SSL.

Data Type

string

Default Value

""

Remarks

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:

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.

Schema

This section provides a complete list of schema properties you can configure.

Location

A path to the directory that contains the schema files defining tables, views, and stored procedures.

Data Type

string

Default Value

%APPDATA%\ApacheCouchDB Data Provider\Schema

Remarks

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%\ApacheCouchDB Data Provider\Schema" with %APPDATA% being set to the user's configuration directory:

BrowsableSchemas

This property restricts the schemas reported to a subset of the available schemas. For example, BrowsableSchemas=SchemaA,SchemaB,SchemaC.

Data Type

string

Default Value

""

Remarks

Listing the schemas from databases can be expensive. Providing a list of schemas in the connection string improves the performance.

Tables

This property restricts the tables reported to a subset of the available tables. For example, Tables=TableA,TableB,TableC.

Data Type

string

Default Value

""

Remarks

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.

Views

Restricts the views reported to a subset of the available tables. For example, Views=ViewA,ViewB,ViewC.

Data Type

string

Default Value

""

Remarks

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.

ListViews

Whether to list views from Apache CouchDB or not.

Data Type

bool

Default Value

false

Remarks

Set this property to true for Apache CouchDB views to show up when listing tables.

Miscellaneous

This section provides a complete list of miscellaneous properties you can configure.

FlattenArrays

Set FlattenArrays to the number of array elements to flatten into columns. Otherwise, arrays are returned as JSON strings.

Data Type

string

Default Value

""

Remarks

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: Set FlattenArrays to the number of elements you want to return from nested arrays. The zero-based index is concatenated to the column name with a dot or the character specified by SeparatorCharacter. 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:

Setting FlattenArrays to -1 will flatten all the elements of nested arrays.

Using FlattenArrays is only recommended for arrays that are expected to be short. See NoSQL Database for other ways to access nested arrays.

FlattenObjects

Set FlattenObjects to true to flatten object properties into columns of their own. Otherwise, embedded objects as raw JSON strings.

Data Type

bool

Default Value

true

Remarks

The property name is concatenated onto the object name with a dot or the character specified by SeparatorCharacter.

For example, you can flatten the nested objects below at connection time:

[
  { "grade": "A", "score": 2 },
  { "grade": "A", "score": 6 },
  { "grade": "A", "score": 10 },
  { "grade": "A", "score": 9 },
  { "grade": "B", "score": 14 }
]

When FlattenObjects is set to true and FlattenArrays is set to 1, the preceding array is flattened into the following table:

FlexibleSchema

Set FlexibleSchema to true to scan for additional metadata on the query result set. Otherwise, the metadata will remain the same.

Data Type

bool

Default Value

true

Remarks

If false, the metadata will remain the same.

MaxRows

Limits the number of rows returned when no aggregation or GROUP BY is used in the query. This takes precedence over LIMIT clauses.

Data Type

int

Default Value

-1

Remarks

Limits the number of rows returned when no aggregation or GROUP BY is used in the query. This takes precedence over LIMIT clauses.

Other

These hidden properties are used only in specific use cases.

Data Type

string

Default Value

""

Remarks

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.

Integration and Formatting

Pagesize

The maximum number of results to return per page from Apache CouchDB.

Data Type

int

Default Value

1000

Remarks

The Pagesize property affects the maximum number of results to return per page from Apache CouchDB. Setting a higher value may result in better performance at the cost of additional memory allocated per page consumed.

PseudoColumns

This property indicates whether or not to include pseudo columns as columns to the table.

Data Type

string

Default Value

""

Remarks

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, "*=*".

RowScanDepth

The maximum number of rows to scan to look for the columns available in a table.

Data Type

int

Default Value

50

Remarks

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.

SeparatorCharacter

The character or characters used to denote hierarchy.

Data Type

string

Default Value

.

Remarks

In order to flatten out hierarchical structures, the connector needs some specifier that states the path to a column through the hierarchy. If this value is "." and a column comes back with the name address.city, this indicates that there is a mapped attribute with a child called city. If your data has columns that already use a single period within the attribute name, set the SeparatorCharacter to a different character or characters.

Timeout

The value in seconds until the timeout error is thrown, canceling the operation.

Data Type

int

Default Value

60

Remarks

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.

TypeDetectionScheme

Determines how the provider will scan the data to determine the fields and data types in each document collection.

Data Type

string

Default Value

RowScan

Remarks

Since Apache CouchDB is schema-less, the columns in a table must be determined by scanning table rows. Set TypeDetectionScheme to toggle the automatic discovery of data types. Set RowScanDepth to configure type detection.

See Also

Type detection is part of Automatic Schema Discovery. Set FlattenArrays and FlattenObjects to configure how the connector projects columns over the hierarchical data.

You can fine-tune the discovered columns and data types by calling CreateSchema to generate a schema file. Schema files have a simple format that makes it easy to change column behavior.

UserDefinedViews

A filepath pointing to the JSON configuration file containing your custom views.

Data Type

string

Default Value

""

Remarks

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:

• Each root element defines the name of a view.
• Each root element contains a child element, called query, which contains the custom SQL query for the view.

For example:

{
    "MyView": {
        "query": "SELECT * FROM Movies 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

Note that the specified path is not embedded in quotation marks.