tBigQueryInput properties for Apache Spark Streaming - 6.5

Big Query

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Data Governance > Third-party systems > Cloud storages > Google BigQuery components
Data Quality and Preparation > Third-party systems > Cloud storages > Google BigQuery components
Design and Development > Third-party systems > Cloud storages > Google BigQuery components

These properties are used to configure tBigQueryInput running in the Spark Streaming Job framework.

The Spark Streaming tBigQueryInput component belongs to the Databases family.

The component in this framework is available in Talend Real Time Big Data Platform and Talend Data Fabric.

Basic settings

Source type

Select the way you want tBigQueryInput to read data from BigQuery:
  • Table: copy the whole table.

  • Query: write a query to select data.

Schema and Edit Schema

A schema is a row description. It defines the number of fields (columns) to Repository. When you create a Spark Job, avoid the reserved word line when naming the fields.

Click Edit schema to make changes to the schema. If the current schema is of the Repository type, three options are available:

  • View schema: choose this option to view the schema only.

  • Change to built-in property: choose this option to change the schema to Built-in for local changes.

  • Update repository connection: choose this option to change the schema stored in the repository and decide whether to propagate the changes to all the Jobs upon completion. If you just want to propagate the changes to the current Job, you can select No upon completion and choose this schema metadata again in the [Repository Content] window.

 

Built-In: You create and store the schema locally for this component only.

 

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs.

When the Source type is Table:

Project ID

If your BigQuery service uses the Google Cloud Platform project ID, keep this check box clear to allow tBigQueryInput to read this ID from the Spark configuration tab or the tBigQueryConfiguration component.

If the BigQuery service uses a custom ID, select this check box and enter the ID.

The ID of your project can be found in the URL of the Google API Console, or by hovering your mouse pointer over the name of the project in the BigQuery Browser Tool.

Dataset

Enter the name of the dataset to which the table to be copied belongs.

When you use BigQuery with Dataproc, in Google Cloud Platform, select the same region for your BigQuery dataset as for the Dataproc cluster to be run.

Table

Enter the name of the table to be copied.

When the Source type is Query:

Query

Enter the query to be used.

When you use BigQuery with Dataproc, in Google Cloud Platform, select the same region for your BigQuery dataset as for the Dataproc cluster to be run.

Usage

Usage rule

This is an input component. It sends data extracted from BigQuery to the component that follows it.

Place a tBigQueryConfiguration component in the same Job because it needs to use the BigQuery configuration information provided by tBigQueryConfiguration.

Spark Connection

You need to use the Spark Configuration tab in the Run view to define the connection to a given Spark cluster for the whole Job. In addition, since the Job expects its dependent jar files for execution, you must specify the directory in the file system to which these jar files are transferred so that Spark can access these files:
  • Yarn mode: when using Google Dataproc, specify a bucket in the Google Storage staging bucket field in the Spark configuration tab; when using other distributions, use a tHDFSConfiguration component to specify the directory.

  • Standalone mode: you need to choose the configuration component depending on the file system you are using, such as tHDFSConfiguration or tS3Configuration.

This connection is effective on a per-Job basis.