IBM Cloudant Connection Details¶

Introduction¶

Connector Version

This documentation is based on version 23.0.8803 of the connector.

Get Started¶

Cloudant Version Support

The connector leverages the Cloudant API to enable bidirectional access to Cloudant data through standard SQL. See Query Mapping for SQL-to-Cloudant-query mappings and more information about accessing unstructured data in Cloudant through SQL.

Establish a Connection¶

Authenticate to Cloudant¶

Cloudant supports three type of authentication:

• Auto (default): the connector decides how to authenticate you, based on

  the other connection properties you have set.

• Basic: Basic username/password authentication. Set AuthScheme to Basic.

• OAuth: Performs authentication based on the OAuth standard. Set AuthScheme to OAuth and supply the values for the Cloudant instance APIKey and URL.

IBM Cloudant Legacy¶

To connect via IBM Cloudant Legacy, ensure that you have a valid IBM Cloudant service credential.

To create an IBM Cloudant service credential:

1. Log in to the IBM Cloud dashboard.
2. Navigate to the Menu icon > Resource List, and open your IBM Cloudant service instance.
3. In the menu, click Service credentials.
4. Click New credential. Cloudant displays a Add new credential window.
5. Enter a name for the new credential.
6. Click Add. Your credentials are added to the Service credentials table.
7. Click Actions > View credentials.
8. Extract the values for User and Password from the JSON file.

Use the values you just obtained to set the User and Password.

Authenticate to a Local Instance¶

Cloudant supports authenticating to data in local instances from version 1.1.0 and above. To authenticate to your local instance, set these parameters:

1. URL: The Url of your local instance. For example: http://localhost:8006
2. User: Your username.
3. Password: Your password.

Fine-Tuning Data Access¶

Fine-Tuning Data Access¶

You can use the following properties to gain control over column behavior in Automatic Schema Discovery.

• RowScanDepth: This property determines the number of rows that will be scanned to detect column data types when generating table metadata.
• TypeDetectionScheme: This property allows more control over the strategy implemented by the RowScanDepth property.

Important Notes¶

Configuration Files and Their Paths¶

• All references to adding configuration files and their paths refer to files and locations on the Harmony 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¶

Cloudant is a schemaless 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.

The connector models the schemaless Cloudant objects into relational tables and translates SQL queries into Cloudant queries to get the requested data. See Query Mapping for more details on how various Cloudant operations are represented as SQL.

The Automatic Schema Discovery scheme automatically finds the data types in a Cloudant 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 Cloudant.

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.

The connector supports listing Cloudant 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 Cloudant views to be displayed when listing tables.

Automatic Schema Discovery¶

The connector automatically infers a relational schema by inspecting a series of Cloudant 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 Cloudant data. JSON Functions enable you to use standard JSON functions to summarize Cloudant 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 Cloudant documents -- this type of query is supported through the Cloudant 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 Cloudant 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)

Cloudant 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'

Cloudant 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'

Cloudant 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 Cloudant:

• 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:cloudant: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¶

Stored Procedures¶

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

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

Jitterbit Connector for Cloudant Stored Procedures¶

CreateSchema¶

Creates a schema definition of a table in Cloudant. Control column discovery with 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¶

GetOAuthAccessToken¶

Gets an authentication token from IBM Cloud. The connection property ApiKey must be specified when calling this stored procedure.

Result Set Columns¶

RefreshOAuthAccessToken¶

Refreshes the OAuth access token used for authentication with IBM Cloud. The connection property ApiKey must be specified when calling this stored procedure.

Input¶

Result Set Columns¶

Advanced Features¶

This section details a selection of advanced features of the Cloudant connector.

User Defined Views

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.

SSL Configuration

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.

Proxy

To configure the connector using Private Agent proxy settings, select the Use Proxy Settings checkbox on the connection configuration screen.

Query Processing

The connector offloads as much of the SELECT statement processing as possible to Cloudant and then processes the rest of the query in memory (client-side).

User Defined Views¶

The Jitterbit Connector for Cloudant 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:

• Create a JSON-formatted configuration file defining the views you want.
• DDL statements.

Define Views Using a Configuration File¶

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"

Define Views Using DDL Statements¶

The connector is also capable of creating and altering the schema via DDL Statements such as CREATE LOCAL VIEW, ALTER LOCAL VIEW, and DROP LOCAL VIEW.

Create a View¶

To create a new view using DDL statements, provide the view name and query as follows:

CREATE LOCAL VIEW [MyViewName] AS SELECT * FROM Customers LIMIT 20;

If no JSON file exists, the above code creates one. The view is then created in the JSON configuration file and is now discoverable. The JSON file location is specified by the UserDefinedViews connection property.

Alter a View¶

To alter an existing view, provide the name of an existing view alongside the new query you would like to use instead:

ALTER LOCAL VIEW [MyViewName] AS SELECT * FROM Customers WHERE TimeModified > '3/1/2020';

The view is then updated in the JSON configuration file.

Drop a View¶

To drop an existing view, provide the name of an existing schema alongside the new query you would like to use instead.

DROP LOCAL VIEW [MyViewName]

This removes the view from the JSON configuration file. It can no longer be queried.

Schema for User Defined Views¶

User Defined Views are exposed in the UserViews schema by default. This is done to avoid the view's name clashing with an actual entity in the data model. You can change the name of the schema used for UserViews by setting the UserViewsSchemaName property.

Work with User Defined Views¶

For example, a SQL statement with a User Defined View called UserViews.RCustomers only lists customers in Raleigh:

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.

SSL Configuration¶

Customize the SSL Configuration¶

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.

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

OAuth

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 Cloudant.

Possible Values¶

Auto, Basic, OAuth

Data Type¶

string

Default Value¶

Auto

Remarks¶

• Auto: Lets the driver decide automatically based on the other connection properties you have set.
• Basic: Set this to use BASIC user / password authentication.
• OAuth: Set this to perform OAuth authentication. For this method you will need the APIKey and URL of Cloudant instance.

URL¶

The URL used to connect to the Cloudant.

Data Type¶

string

Default Value¶

""

Remarks¶

The HTTP or HTTPS URL used to connect to the Cloudant in the format https://{instance id}-bluemix.cloudantnosqldb.appdomain.cloud or in case of self hosting server http[s]://{server}:{port}

User¶

The Cloudant user account used to authenticate.

Data Type¶

string

Default Value¶

""

Remarks¶

Together with Password, this field is used to authenticate against the Cloudant 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.

ApiKey¶

The API Key used to identify the user to IBM Cloud.

Data Type¶

string

Default Value¶

""

Remarks¶

Access to resources in the Cloudant REST API is governed by an API key in order to retrieve token. An API Key created by navigating to Manage --> Access (IAM) --> Users and clicking 'Create'.

OAuth¶

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

InitiateOAuth¶

Set this property to initiate the process to obtain or refresh the OAuth access token when you connect.

Possible Values¶

OFF, GETANDREFRESH, REFRESH

Data Type¶

string

Default Value¶

OFF

Remarks¶

The following options are available:

1. OFF: Indicates that the OAuth flow will be handled entirely by the user. An OAuthAccessToken will be required to authenticate.
2. GETANDREFRESH: Indicates that the entire OAuth Flow will be handled by the connector. If no token currently exists, it will be obtained by prompting the user via the browser. If a token exists, it will be refreshed when applicable.
3. REFRESH: Indicates that the connector will only handle refreshing the OAuthAccessToken. The user will never be prompted by the connector to authenticate via the browser. The user must handle obtaining the OAuthAccessToken and OAuthRefreshToken initially.

OAuthSettingsLocation¶

The location of the settings file where OAuth values are saved when InitiateOAuth is set to GETANDREFRESH or REFRESH . Alternatively, you can hold this location in memory by specifying a value starting with 'memory://'.

Data Type¶

string

Default Value¶

%APPDATA%\Cloudant Data Provider\OAuthSettings.txt

Remarks¶

When InitiateOAuth is set to GETANDREFRESH or REFRESH, the connector saves OAuth values to avoid requiring the user to manually enter OAuth connection properties and to allow the credentials to be shared across connections or processes.

Instead of specifying a file path, you can use memory storage. Memory locations are specified by using a value starting with 'memory://' followed by a unique identifier for that set of credentials (for example, memory://user1). The identifier can be anything you choose but should be unique to the user. Unlike file-based storage, where credentials persist across connections, memory storage loads the credentials into static memory, and the credentials are shared between connections using the same identifier for the life of the process. To persist credentials outside the current process, you must manually store the credentials prior to closing the connection. This enables you to set them in the connection when the process is started again. You can retrieve OAuth property values with a query to the sys_connection_props system table. If there are multiple connections using the same credentials, the properties are read from the previously closed connection.

The default location is "%APPDATA%\Cloudant Data Provider\OAuthSettings.txt" with %APPDATA% set to the user's configuration directory. The default values are

• Windows: "register://%DSN"
• Unix: "%AppData%..."
• Mac: "%AppData%..."

where DSN is the name of the current DSN used in the open connection.

The following table lists the value of %APPDATA% by OS:

OAuthRefreshToken¶

The OAuth refresh token for the corresponding OAuth access token.

Data Type¶

string

Default Value¶

""

Remarks¶

The OAuthRefreshToken property is used to refresh the OAuthAccessToken when using OAuth authentication.

OAuthExpiresIn¶

The lifetime in seconds of the OAuth AccessToken.

Data Type¶

string

Default Value¶

""

Remarks¶

Pair with OAuthTokenTimestamp to determine when the AccessToken will expire.

OAuthTokenTimestamp¶

The Unix epoch timestamp in milliseconds when the current Access Token was created.

Data Type¶

string

Default Value¶

""

Remarks¶

Pair with OAuthExpiresIn to determine when the AccessToken will expire.

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%\Cloudant 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%\Cloudant 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 Cloudant or not.

Data Type¶

bool

Default Value¶

false

Remarks¶

Set this property to true for Cloudant 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¶

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

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

Data Type¶

int

Default Value¶

1000

Remarks¶

The Pagesize property affects the maximum number of results to return per page from Cloudant. 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¶

Option for 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 Cloudant is schemaless, 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.