Google BigQuery Connectors

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Google BigQuery V2 sources in mappings

To read data from Google BigQuery, configure a Google BigQuery object as the Source transformation in a mapping.

Specify the name and description of Google BigQuery source. Configure the source and advanced properties for the source object in mappings.

The following table describes the source properties that you can configure for a Google BigQuery source:

Property	Description
Connection	Name of the Google BigQuery V2 source connection. Select a source connection, or click New Parameter to define a new parameter for the source connection. If you want to overwrite the parameter at runtime, select the Allow parameter to be overridden at run time option when you create a parameter.
Source Type	Type of the Google BigQuery source object. Select Single Object , Multiple Objects¹ , Query¹ or Parameter . When you select single object as the source type, you can choose a table or view. For the other source object types, you can choose a table.
Object	Name of the Google BigQuery source object based on the source type selected.
Parameter	A parameter file where you define values that you want to update without having to edit the task. Select an existing parameter for the source object or click New Parameter to define a new parameter for the source object. The Parameter property appears only if you select Parameter as the source type. If you want to overwrite the parameter at runtime, select the Allow parameter to be overridden at run time option when you create a parameter. When the task runs, the agent uses the parameters from the file that you specify in the task advanced session properties.
Query¹	Click on Define Query and enter a valid custom query. The Query property appears only if you select Query as the source type. You can parameterize a custom query object at runtime in a mapping. Select the source advanced property Use EXPORT DATA Statement to stage to use the ORDER BY clause in a custom query in staging mode.
Filter	Configure a simple filter or an advanced filter to remove rows at the source. You can improve efficiency by filtering early in the data flow. A simple filter includes a field name, operator, and value. Use an advanced filter to define a more complex filter condition, which can include multiple conditions using the AND or OR logical operators. Only simple filter is applicable for mappings in advanced mode.
¹ Doesn't apply to mappings in advanced mode.

The following table describes the advanced properties that you can configure for a Google BigQuery source:

Property	Description
Source Dataset ID	Optional. Overrides the Google BigQuery dataset name that you specified in the Source transformation.
Source Table Name	Optional. Overrides the Google BigQuery table name that you specified in the Source transformation.
Source Staging Dataset¹	Optional. Overrides the Google BigQuery staging dataset name that you specified in the connection and the Source Dataset ID source advanced property.
Number of Rows to Read	Specifies the number of rows to read from the Google BigQuery source table.
Allow Large Results¹	Determines whether Google BigQuery V2 Connector must produce arbitrarily large result tables to query large source tables. If you select this option, you must specify a destination table to store the query results.
Query Results Table Name¹	Required if you select the Allow Large Results option. Specifies the destination table name to store the query results. If the table is not present in the dataset, Google BigQuery V2 Connector creates the destination table with the name that you specify.
Job Poll Interval In Seconds¹	The number of seconds after which Google BigQuery V2 Connector polls the status of the read job operation. Default is 10.
Read Mode	Specifies the read mode to read data from the Google BigQuery source. You can select one the following read modes: Direct. In direct mode, Google BigQuery V2 Connector reads data directly from the Google BigQuery source table. When you use hybrid and complex connection mode, you cannot use direct mode to read data from the Google BigQuery source. Staging¹. In staging mode, Google BigQuery V2 Connector exports data from the Google BigQuery source into Google Cloud Storage. After the export is complete, Google BigQuery V2 Connector downloads the data from Google Cloud Storage into the local stage file and then reads data from the local stage file. Default is Direct mode.
Use EXPORT DATA statement to stage	Uses the EXPORT DATA statement to export data from Google BigQuery to Google Cloud Storage. If the query contains an ORDER BY clause, the specified order is maintained when you export the data. This property applies to staging mode.
Number of Threads for Downloading Staging Files¹	Specifies the number of files that Google BigQuery V2 Connector downloads at a time to enable parallel download. This property applies to staging mode.
Data format of the staging file¹	Specifies the data format of the staging file. You can select one of the following data formats: Avro JSON (Newline Delimited). Supports flat and record data with nested and repeated fields. CSV. Supports flat data. In a .csv file, columns of the Timestamp data type are represented as floating point numbers that cause the milliseconds value to differ. Parquet This property applies to staging mode.
Local Stage File Directory¹	Specifies the directory on your local machine where Google BigQuery V2 Connector stores the Google BigQuery source data temporarily before it reads the data. This property applies to staging mode. This property is not applicable when you use a serverless runtime environment.
Staging File Name¹	Name of the staging file where data from the Google BigQuery source table is exported to Google Cloud Storage. This property applies to staging mode.
Enable Staging File Compression¹	Indicates whether to compress the size of the staging file in Google Cloud Storage before Google BigQuery V2 Connector reads data from the staging file. You can enable staging file compression to reduce cost and transfer time. This property applies to staging mode.
Persist Extract Staging File After Download¹	Indicates whether Google BigQuery V2 Connector must persist the staging file after it reads data from the staging file. By default, Google BigQuery V2 Connector deletes the staging file.
Persist Destination Table¹	Indicates whether Google BigQuery V2 Connector must persist the query results table after it reads data from the query results table. By default, Google BigQuery V2 Connector deletes the query results table.
pre SQL¹	SQL statement that you want to run before reading data from the source. For example, if you want to select records in the database before you read the records from the table, specify the following pre SQL statement: SELECT * FROM [api-project-80697026669:EMPLOYEE.DEPARTMENT] LIMIT 1000;
post SQL¹	SQL statement that you want to run after reading data from the source. For example, if you want to update records in a table after you read the records from a source table, specify the following post SQL statement: UPDATE [api-project-80697026669.EMPLOYEE.PERSONS_TGT_DEL] SET phoneNumber.number=1000011, phoneNumber.areaCode=100 where fullname='John Doe'
pre SQL Configuration¹	Specify a pre SQL configuration. For example, DestinationTable:PRESQL_SRC,DestinationDataset:EMPLOYEE, FlattenResults:False,WriteDisposition:WRITE_TRUNCATE,UseLegacySql:False
post SQL Configuration¹	Specify a post SQL configuration. For example, DestinationTable:POSTSQL_SRC,DestinationDataset:EMPLOYEE, FlattenResults:True,WriteDisposition:WRITE_TRUNCATE,UseLegacySql:False
SQL Override Query¹	Overrides the default SQL query used to read data from the Google BigQuery source. When you specify SQL override query, you must specify a dataset name in the Source Dataset ID advanced source property. Ensure that the list of selected columns, data types, and the order of the columns that appear in the query matches the columns, data types, and order in which they appear in the source object. Ensure that you only map all the columns in the SQL override query to the target. Does not apply when you enable partitioning. Select the source advanced property Use EXPORT DATA Statement to stage to use the ORDER BY clause in a SQL Override Query in staging mode. When staging optimization is enabled in a mapping, the columns mapped in the SQL Override Query must match the columns in the source object.
Use Legacy SQL For SQL Override¹	Indicates that the SQL Override query is specified in legacy SQL. Use the following format to specify a legacy SQL query for the SQL Override Query property: SELECT <Col1, Col2, Col3> FROM [projectID:datasetID.tableName] Clear this option to define a standard SQL override query. Use the following format to specify a standard SQL query for the SQL Override Query property: SELECT * FROM `projectID.datasetID.tableName`
Label¹	You can assign a label for the transformation to organize and filter the associated jobs in the Google Cloud Platform Log Explorer. For more information about labels and their usage requirements, see Assign a label to the transformations.
Billing Project ID¹	The project ID for the Google Cloud project that is linked to an active Google Cloud Billing account where the Secure Agent runs query and extract jobs. If you omit the project ID here, the Secure Agent runs query and extract jobs in the Google Cloud project corresponding to the Project ID value specified in the Google BigQuery V2 connection.
Retry Options¹	Comma-separated list to specify the following retry options if you set Direct as the read mode: Retry Count. The number of retry attempts to read data from Google BigQuery. Retry Interval. The time in seconds to wait between each retry attempt. Retry Exceptions. The list of exceptions separated by pipe (\|) character for which the retries are made. Use the following format to specify the retry options: For example, RetryCount:5,RetryInterval:1,RetryExceptions:java.net.ConnectException\|java.io.IOException The retry options are available for preview. Preview functionality is supported for evaluation purposes but is unwarranted and is not production-ready. Informatica recommends that you use in non-production environments only. Informatica intends to include the preview functionality in an upcoming release for production use, but might choose not to in accordance with changing market or technical circumstances. For more information, contact Informatica Global Customer Support. To use the functionality, your organization must have the appropriate licenses.
Number of Spark Partitions²	Specifies the maximum number of partitions that the Spark engine splits the data into. Default is 1.
¹ Doesn't apply to mappings in advanced mode. ² Applies only to mappings in advanced mode.

You can set the tracing level in the advanced properties session to determine the amount of details that logs contain.

The following table describes the tracing levels that you can configure:

Property	Description
Terse	The Secure Agent logs initialization information, error messages, and notification of rejected data.
Normal	The Secure Agent logs initialization and status information, errors encountered, and skipped rows due to transformation row errors. Summarizes session results, but not at the level of individual rows.
Verbose Initialization	In addition to normal tracing, the Secure Agent logs additional initialization details, names of index and data files used, and detailed transformation statistics.
Verbose Data	In addition to verbose initialization tracing, the Secure Agent logs each row that passes into the mapping. Also notes where the Secure Agent truncates string data to fit the precision of a column and provides detailed transformation statistics. When you configure the tracing level to verbose data, the Secure Agent writes row data for all rows in a block when it processes a transformation.