GoogleBigQueryConnector

Categories

Integrations

Web

Related Transformers

AmazonAthenaConnector

GoogleCloudPubSubConnector

GoogleCloudStorageConnector

GoogleDriveConnector

GoogleLanguageConnector

GoogleVisionConnector

Accesses the Google BigQuery service to load or query tables from a Google Cloud account.

Jump to Configuration

Typical Uses

  • Load CSV formatted data into new or existing BigQuery tables
  • Query BigQuery tables with the option to load the result to a specified destination BigQuery table

How does it work?

Google BigQuery is a managed NoSQL database service.

The GoogleBigQueryConnector uses your Google Cloud account credentials (either via a previously defined FME web connection, or by setting up a new FME web connection right from the transformer).

For more information about BigQuery, please visit the Google Cloud BigQuery product page.

Configuration

Input Ports

This transformer accepts any feature.

Output Ports

The output of this transformer will vary depending on the Request > Action performed.

  • After a Load Data action, output will include the following attributes:

_project_id

Name of the project_id loaded into.

_table

Name of the table loaded into.

_dataset

Name of the dataset loaded into.

_rows_written

Number of rows written to the specified table in the dataset.
  • After a Query action, output will contain attributes set in the Exposed Attributes parameter, which correspond to the columns from the ran query. Geography functions will output as WKT (well-known text).

The incoming feature is output through this port.

Features that cause the operation to fail are output through this port. An fme_rejection_code attribute, will be added, along with a more descriptive fme_rejection_message attribute which contains more specific details as to the reason for the failure.

Note: If a feature comes in to the GoogleBigQueryConnector already having a value for fme_rejection_code, this value will be removed.

Rejected Feature Handling: can be set to either terminate the translation or continue running when it encounters a rejected feature. This setting is available both as a default FME option and as a workspace parameter.

Parameters

Credential Source

Credentials can be used from different sources. Using a web connection integrates best with FME but in some cases, you may wish to use one of the other sources.

  • Web Connection: Use a Google BigQuery web connection stored in the FME web connections database.
  • Service Account Key File: Use credentials already configured on the system, in the key file specified in the environment variable GOOGLE_APPLICATION_CREDENTIALS.
Account

Available when the credential source is Web Connection. To create a Google BigQuery web connection, click the Account drop-down box and select Add Web Connection.

The connection can then be managed via Tools > FME Options > Web Connections.

Project ID The Google Cloud project id. Only required when the credential source is Web Connection.
Action

The type of operation to perform. Choices include:

  • Load Data: load data into BigQuery tables and datasets
  • Query: query a BigQuery table and dataset

Data Source

Load Source

Select the type of source data to be loaded:

  • File
  • Google Storage

File to Load

If Load Source is File, specify the location and name of the file to be loaded.

Bucket

If Load Source is Google Storage, specify the Google storage bucket.

Path

If Load Source is Google Storage, specify the Google storage path.

File Type

Only CSV is supported at this time.

Header Rows to Skip

For CSV files, specify the number of rows to skip at the top of the file.

For example, if the file contains a single-line header, enter 1.

Auto Detect Schema

If Yes ,BigQuery will at best effort detect and set the data types of your data.

If No, Defined Schema will be used.

Defined Schema

If Auto Detect Schema is No, define a schema using the following JSON format.

[

{

"description": "[DESCRIPTION]",

"name": "[NAME]",

"type": "[TYPE]",

"mode": "[MODE]"

},

{

"description": "[DESCRIPTION]",

"name": "[NAME]",

"type": "[TYPE]",

"mode": "[MODE]"

}

]

For more information, see BigQuery's Specifying a schema documentation.

Load Options

Table Handling

If the specified Destination Table does not exist, it will be created.

If it does already exist, the selected method will be used to load data:

  • Overwrite: Replaces all existing data in the table.
  • Append: Appends the data to the end of the table.
  • Write if Empty: Loads the data only if the table is empty.

Destination Dataset

The dataset of the destination table.

Destination Table

The target table where results are loaded.

Query Options

Query

The SQL query to run.

Note that when querying the BigQuery type NUMERIC, FME will receive the type fme_string.

Enable Destination Table

If enabled, query results will be stored in a table.

Table Handling

If the specified Destination Table does not exist, it will be created.

If it does already exist, the selected method will be used to load data:

  • Overwrite: Replaces all existing data in the table.
  • Append: Appends the data to the end of the table.
  • Write if Empty: Loads the data only if the table is empty.

Destination Dataset

The dataset of the destination table.

Destination Table

The target table where results are loaded.

Exposed Attributes

Exposed Attributes

The list of attributes to output. Attributes should be the column names of the query.

Editing Transformer Parameters

Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click beside the applicable parameter. For more information, see Transformer Parameter Menu Options.

Defining Values

There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters. There are a number of tools and shortcuts that can assist in constructing values, generally available from the drop-down context menu adjacent to the value field.

Using the Text Editor

The Text Editor provides a convenient way to construct text strings (including regular expressions) from various data sources, such as attributes, parameters, and constants, where the result is used directly inside a parameter.

Text Editor

Using the Arithmetic Editor

The Arithmetic Editor provides a convenient way to construct math expressions from various data sources, such as attributes, parameters, and feature functions, where the result is used directly inside a parameter.

Arithmetic Editor

Conditional Values

Set values depending on one or more test conditions that either pass or fail.

Parameter Condition Definition Dialog

Content

Expressions and strings can include a number of functions, characters, parameters, and more.

When setting values - whether entered directly in a parameter or constructed using one of the editors - strings and expressions containing String, Math, Date/Time or FME Feature Functions will have those functions evaluated. Therefore, the names of these functions (in the form @<function_name>) should not be used as literal string values.

String Functions

These functions manipulate and format strings.

Special Characters

 A set of control characters is available in the Text Editor.

Math Functions

Math functions are available in both editors.
Date/Time Functions Date and time functions are available in the Text Editor.

Math Operators

These operators are available in the Arithmetic Editor.

FME Feature Functions

These return primarily feature-specific values.

FME Parameters

FME and workspace-specific parameters may be used.
Creating and Modifying User Parameters Create your own editable parameters.

Dialog Options - Tables

Transformers with table-style parameters have additional tools for populating and manipulating values.

Row Reordering

Enabled once you have clicked on a row item. Choices include:

  • Add a row
  • Remove a row
  • Move current row up one
  • Move current row down one
  • Move current row to top
  • Move current row to bottom

Cut, Copy, and Paste

Enabled once you have clicked on a row item. Choices include:

  • Cut a row - delete and copy to clipboard
  • Copy a row to the clipboard
  • Paste a row from the clipboard

Cut, copy, and paste may be used within a transformer, or between transformers.

Filter

Start typing a string, and the matrix will only display rows matching those characters. Searches all columns. This only affects the display of attributes within the transformer - it does not alter which attributes are output.

Import

Import populates the table with a set of new attributes read from a dataset. Specific application varies between transformers.

Reset/Refresh

Generally resets the table to its initial state, and may provide additional options to remove invalid entries. Behavior varies between transformers.

Note: Not all tools are available in all transformers.

Reference

Processing Behavior

Feature-Based

Feature Holding

No
Dependencies Google Cloud Storage Account
FME Licensing Level FME Base Edition and above
Aliases  
History Released FME 2019.1

FME Community

The FME Community is the place for demos, how-tos, articles, FAQs, and more. Get answers to your questions, learn from other users, and suggest, vote, and comment on new features.

Search for all results about the GoogleBigQueryConnector on the FME Community.

 

Examples may contain information licensed under the Open Government Licence – Vancouver