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Creating a test case

Use the following URI to create a test case:

POST /datavalidation-service/api/v1/testcase

Use the IDS-SESSION-ID header in the POST request.

POST request

Use the following fields in the POST request:

Field	Required?	Description
testCaseName	Yes	Name of the test case.
description	No	Description of the test case.
leftObjectType	Yes	Type of the data source. Specify one of the following values: OBJECT . Indicates that the data source is a table or view. SAVED_SQL_QUERY . Indicates that the data source is a saved SQL query.
leftConnId	Yes	Connection ID of the first connection. When you open the connection in Administrator, the numeric value that you see in the URL is the connection ID. For example, if the URL is <Informatica Intelligent Cloud Services URL>/cloudUI/products/administer/main/ConnectionDetailsWS/014N8B0B000000000898/read , the connection ID is 014N8B0B000000000898 .
leftSavedSqlQuery	No	ID of the saved SQL query of the first connection. Use the following format: "leftSavedSqlQuery" : { "id" : <value> }
leftTableName	No	Table name of the first connection.
leftTablePk	Yes	Primary key of the table in the first connection. You can also enter multiple keys.
rightObjectType	Yes	Type of the data source. Specify one of the following values: OBJECT . Indicates that the data source is a table or view. SAVED_SQL_QUERY . Indicates that the data source is a saved SQL query.
rightConnId	Yes	Connection ID of the second connection. When you open the connection in Administrator, the numeric value that you see in the URL is the connection ID. For example, if the URL is <Informatica Intelligent Cloud Services URL>/cloudUI/products/administer/main/ConnectionDetailsWS/014N8B0B000000000898/read , the connection ID is 014N8B0B000000000898 .
rightSavedSqlQuery	No	ID of the saved SQL query of the second connection. Use the following format: "rightSavedSqlQuery" : { "id" : <value> }
rightTableName	No	Table name of the second connection.
rightTablePk	Yes	Primary key of the table in the second connection. You can also enter multiple keys.
runtimeEnvId	Yes	Runtime environment where the test case runs.
stagingConnectionId	Yes	Connection ID of the flat file connection that Data Validation uses to stores reports. When you open the flat file connection in Administrator, the numeric value that you see in the URL is the connection ID. For example, if the URL is <Informatica Intelligent Cloud Services URL>/cloudUI/products/administer/main/ConnectionDetailsWS/014N8B0B000000000ATW/read , the connection ID is 014N8B0B000000000ATW .
frsDocLocation	Yes	The location to save the test case. To save the test case in a project, use the following syntax: "{\"type\":\"Project\",\"id\":\"<project_ID>\",\"path\":\"<project_name>\"}", To save the test case in a folder, use the following syntax: "{\"type\":\"Folder\",\"id\":\"<folder_ID>\",\"path\":\"<folder_name>\"}", When you open a project, the numeric value that you see in the URL is the project ID. Similarly, when you open a folder, the numeric value that you see in the URL is the folder ID. By default, the test case is saved under the Default project.
emailNotificationStrategy	Yes	Specify one of the following values: ORG. Data Validation uses the default email notification options that are configured in Administrator. CUSTOM. Specify the email addresses that Data Validation must use for the success and failure email notifications. Separate multiple email addresses with a comma. NONE. Data Validation doesn't send email notifications.
successEmails	Required if emailNotificationStrategy is set to CUSTOM	Specify the email addresses that Data Validation must use for the success email notifications. Separate multiple email addresses with a comma.
errorEmails	Required if emailNotificationStrategy is set to CUSTOM	Specify the email addresses that Data Validation must use for the failure email notifications. Separate multiple email addresses with a comma.
leftConnPath	Required for Amazon Redshift v2 and Amazon S3 v2 connections	If you use an Amazon Redshift v2 or an Amazon S3 v2 connection, enter a valid path for the first connection.
leftConnAdvancedParams	No	If you use an Amazon Redshift v2, Amazon S3 v2, or flat file connection, specify the advanced parameters to be used for the first connection. Amazon Redshift v2 For Amazon Redshift v2 connections, specify the S3 bucket name in the advanced parameters. For example, enter: { "S3BucketName": "<value>" } Amazon S3 v2 For Amazon S3 v2 connections, Data Validation supports the Parquet file and flat file formats. For Parquet file format, specify the following advanced parameters: {"formatId":"Parquet","@type":"dataFormat","dataFormatAttributes": {}} For flat file format, specify the following default advanced parameters: { "formatId": "Flat", "@type":"dataFormat", "dataFormatAttributes": { "escapeChar": "<value>", "delimiter": "<value>", "headerLineNumber": <value>, "qualifier": "<value>", "firstDataRow": <value>} } For example: { "formatId": "Flat", "@type": "dataFormat", "dataFormatAttributes": { "escapeChar": "", "delimiter": ",", "headerLineNumber": 1, "qualifier": "\"", "firstDataRow": 2} } Flat file For flat file connections, specify the advanced parameters to determine how the flat file must be parsed.For example, enter: { "srcFFAttrs" :{ "delimiter" : "<value>" , "textQualifier" : "<value>" , "escapeChar" : "<value>" , "headerLineNo" : <value> , "firstDataRow" : <value> }}
rightConnPath	Required for Amazon Redshift v2 and Amazon S3 v2 connections	If you use an Amazon Redshift v2 or an Amazon S3 v2 connection, enter a valid path for the second connection.
rightConnAdvancedParams	No	If you use an Amazon Redshift v2, Amazon S3 v2, or flat file connection, specify the advanced parameters to be used for the second connection. Amazon Redshift v2 For Amazon Redshift v2 connections, specify the S3 bucket name in the advanced parameters. For example, enter: { "S3BucketName": "<value>" } Amazon S3 v2 For Amazon S3 v2 connections, Data Validation supports the Parquet file and flat file formats. For Parquet file format, specify the following advanced parameters: { "formatId":"Parquet", "@type":"dataFormat", "dataFormatAttributes": {} } For flat file format, specify the following default advanced parameters: { "formatId": "Flat", "@type":"dataFormat", "dataFormatAttributes": { "escapeChar": "<value>", "delimiter": "<value>", "headerLineNumber": <value>, "qualifier": "<value>", "firstDataRow": <value>} } For example: { "formatId": "Flat", "@type": "dataFormat", "dataFormatAttributes": { "escapeChar": "", "delimiter": ",", "headerLineNumber": 1, "qualifier": "\"", "firstDataRow": 2} } Flat file For flat file connections, specify the advanced parameters to determine how the flat file must be parsed.For example, enter: { "srcFFAttrs" :{ "delimiter" : "<value>" , "textQualifier" : "<value>" , "escapeChar" : "<value>" , "headerLineNo" : <value> , "firstDataRow" : <value> }}
leftConnWhereClause	No	WHERE clause to be used for the first connection. If you use a WHERE clause, Data Validation selects those rows for sampling that meet the condition specified in the WHERE clause.
rightConnWhereClause	No	WHERE clause to be used for the second connection. If you use a WHERE clause, Data Validation selects those rows for sampling that meet the condition specified in the WHERE clause.
verboseMode	No	Defines the logging level. Enter true to use the verbose mode. The log includes messages of all logging levels. This option is useful for debugging. Enter false to use the standard mode. The log includes only error messages.
keepDIAssets	No	Defines whether you want to save the Data Integration mappings and tasks that Data Validation creates when it runs the test case. Enter true to save the Data Integration assets after the test case run. Enter false if you do not want to save the Data Integration assets after the test case run.
ignoreCase	No	Defines whether you want to ignore casing differences in the data. Enter true to ignore casing differences in the data. Enter false to consider the casing differences in the data as a mismatch.
trimString	No	Defines whether you want to trim leading and trailing white spaces in string values. Enter true to trim leading and trailing white spaces in string values. Enter false to retain leading and trailing white spaces in string values. Default is false .
badRecordLimit	No	Defines the maximum number of unmatched, extra, and missing records to show in the detailed test results. Enter the value as 100 , 500 , or 1000 . Default is 100 .
colMappings	Yes	Defines the name, type, precision, and scale for each column mapping. Use the following syntax to map columns in the first connection and second connection: "colMappings": [ { "aggrFunc": "<function1,function2,functionn>", "leftColName": "<value>", "leftColType": "<value>", "rightColName": "<value>", "rightColType": "<value>", "rightColPrecision": <value>, "rightColScale": <value>, "leftColPrecision": <value>, "leftColScale": <value>, }, { "leftColName": "<value>", "leftColType": "<value>", "rightColName": "<value>", "rightColType": "<value>", "rightColPrecision": <value>, "rightColScale": <value>, "leftColPrecision": <value>, "leftColScale": <value>, "aggrFunc": "min" } ], Use the aggrFunc field to define the aggregation functions that Data Validation must use to compare the table. Separate multiple aggregation functions with a comma. The aggregation function names must be in uppercase. An aggregation functions test retrieves summarized information about the data contained in the data sources. Use aggregation to verify whether all records were moved or to identify incorrect logic in WHERE clauses. Based on the data type of the columns, you can use one or more of the following aggregation functions: COUNT . Counts the number of rows that contain non-null values for a string or numeric column. COUNT_ROWS . Counts the number of rows for a string or numeric column. Includes rows that contain nulls. MIN . Calculates the minimum value for a numeric column. MAX . Calculates the maximum value for a numeric column. AVG . Calculates the average value of a numeric column. SUM . Calculates the total value of a numeric column.
sampling	Yes	Configure data sampling for Data Validation to compare between sample source data and sample target data. The less data that Data Validation samples, the faster the test runs. Use the following syntax to specify the sampling type and value: "sampling": { "type": "<value>", "val": <value> } } Use one of the following options: Enter the type as percentage to sample a percentage of the rows. The test report shows records that are missing or unmatched in the Connection 2 table, but doesn't show extra records if any exist. Enter the val as 1 , 5 , 10 , 25 , 50 , or 75 . For example, enter: "sampling": { "type": "percentage", "val": 25 } } Enter the type as first to sample a defined number of rows at the beginning of the table. Enter the val as 100 , 1000 , or 10000 . For example, enter: "sampling": { "type": "first", "val": 100 } } Enter the type as last to sample a defined number of rows at the end of the table. Enter the val as 100 , 1000 , or 10000 . For example, enter: "sampling": { "type": "last", "val": 1000 } } Enter the type as where_clause to sample those rows that meet the condition specified in the WHERE clause. If you use the where_clause option, you must specify a valid where clause in at least one of the following attributes: leftConnWhereClause rightConnWhereClause

POST request sample

The following snippet shows a POST request sample to create a test case:

{
    "testCaseName": "PCToCDITestCase",
    "frsDocLocation": "{\"type\":\"Project\",\"id\":\"436TU7N2RsicOmYQGVpWAl\",\"path\":\"SG\"}",
    "description": "",
    "leftConnId": "014N8B0B000000000AGX",
    "leftConnType": "Oracle",
    "leftTableName": "EMPS_SNOW",
    "leftTablePk": ["EMPID"],
    "rightConnId": "014N8B0B000000000AGX",
    "rightConnType": "Oracle",
    "leftConnPath": "",
    "rightConnPath": "",
    "leftConnAdvancedParams": {},
    "rightConnAdvancedParams": {},
    "rightTableName": "EMPS_UPPERLOWERCASEFIELD",
    "rightTablePk": ["emp id"],
    "runtimeEnvId": "014N8B25000000000006",
    "stagingConnectionId": "014N8B0B0000000003HI",
    "colMappings": [{
            "aggrFunc": "",
            "leftColName": "NICKNAME",
            "leftColType": "string",
            "leftColPrecision": 100,
            "leftColScale": 0,
            "rightColName": "NICKNAME",
            "rightColType": "string",
            "rightColPrecision": 100,
            "rightColScale": 0
        }, {
            "aggrFunc": "",
            "leftColName": "CITY",
            "leftColType": "string",
            "leftColPrecision": 50,
            "leftColScale": 0,
            "rightColName": "CITY",
            "rightColType": "string",
            "rightColPrecision": 50,
            "rightColScale": 0
        }, {
            "aggrFunc": "",
            "leftColName": "GENDER",
            "leftColType": "string",
            "leftColPrecision": 20,
            "leftColScale": 0,
            "rightColName": "GENDER",
            "rightColType": "string",
            "rightColPrecision": 20,
            "rightColScale": 0
        }, {
            "aggrFunc": "",
            "leftColName": "EMPID",
            "leftColType": "decimal",
            "leftColPrecision": 38,
            "leftColScale": 0,
            "rightColName": "emp id",
            "rightColType": "decimal",
            "rightColPrecision": 38,
            "rightColScale": 0
        }, {
            "aggrFunc": "",
            "leftColName": "NAME",
            "leftColType": "string",
            "leftColPrecision": 200,
            "leftColScale": 0,
            "rightColName": "Full Name",
            "rightColType": "string",
            "rightColPrecision": 200,
            "rightColScale": 0
        }, {
            "aggrFunc": "",
            "leftColName": "SALARY",
            "leftColType": "decimal",
            "leftColPrecision": 9,
            "leftColScale": 1,
            "rightColName": "SALARY1",
            "rightColType": "decimal",
            "rightColPrecision": 9,
            "rightColScale": 1
        }, {
            "aggrFunc": "",
            "leftColName": "ORACLESTATUS",
            "leftColType": "string",
            "leftColPrecision": 70,
            "leftColScale": 0,
            "rightColName": "oracle status",
            "rightColType": "string",
            "rightColPrecision": 70,
            "rightColScale": 0
        }, {
            "aggrFunc": "",
            "leftColName": "ORACLECOMMENTS",
            "leftColType": "string",
            "leftColPrecision": 80,
            "leftColScale": 0,
            "rightColName": "Oracle Commments",
            "rightColType": "string",
            "rightColPrecision": 80,
            "rightColScale": 0
        }
    ],
    "verboseMode": false,
    "keepDIAssets": false,
    "ignoreCase": false,
    "trimString": false,
    "leftConnWhereClause": "",
    "rightConnWhereClause": "",
    "badRecordLimit": 100,
    "successEmails": "",
    "errorEmails": "",
    "emailNotificationStrategy": "NONE"
}

POST response

If the test case was created successfully, the POST request returns a

200 Successful operation

response and returns the following response fields:

Field	Type	Description
testCaseId	String	ID of the test case.
frsDocId	String	ID of the test case in the Informatica repository.
testCaseName	String	Name of the test case.

If the test case creation failed, the POST request returns a

400 Bad request

response or a

500 Internal Server Error

response. It also returns the following response fields:

Field	Type	Description
code	String	Code of the error message.
message	String	Error message.
debugMessage	String	Message that can be used for debugging the issue.
details	String	Detailed information about the error message.

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REST API Reference

REST API Reference

Creating a test case

Creating a test case