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Snap type:

Write

Description:

This Snap allows you to execute queries on BigQuery easily leveraging the jobs and query APIs. This Snap works only with single queries. A complete list of supported queries as well as examples are documented here: https://cloud.google.com/bigquery/query-reference.

Expected upstream Snaps: [None]
Expected downstream Snaps: The Snap will output one document for every record retrieved, hence any document processing Snap can be used downstream. Mapper or any other application where the data returned from the query needs to be written to are examples.
Expected input: [None]
Expected output: Document for each record retrieved. Special types such as TIMESTAMP, TIME are converted into SnapLogic internal date type representations which then can be consumed by downstream Snaps just like any other data type.

Note

title	Snaps in Google BigQuery Snap Pack

Write datetime values to the database tables, always in UTC format.
Convert any non-UTC values in the incoming data to UTC before writing them.
Consider datetime values without the time zone mentioned, as in UTC.

So, ensure that you include the time zone in all the datetime values that you load into Google BigQuery tables using this Snap.

For example: "2020-08-29T18:38:07.370 America/Los_Angeles", “2020-09-11T10:05:14.000-07:00", “2020-09-11T17:05:14.000Z”

Prerequisites:

[None]

Support and limitations: Works in Ultra Task Pipelines.

Known Issues

Google BigQuery does not support very large exponential values—larger than EXP(700). So, while displaying values of such high exponential order in the validation preview, this Snap routes to the error view, and displays the following error:
"Data conversion failed for field f0_(FLOAT) of value Infinity."
The Snap also displays empty output in the preview, which is not expected.

Account:

This Snap uses account references created on the Accounts page of SnapLogic Manager to handle access to this endpoint. See Google BigQuery Account for information on the type of account to use.

Views:

Input	This Snap has at most one document input view.
Output	This Snap has exactly one document output view which displays the result set returned from the query - one document for each record retrieved.
Error	This Snap has at most one document error view and produces zero or more documents in the view.

Settings

Label

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Project ID

Required. This drop-down shows you a list of all the available projects that your user Account has access to. Clicking on the the drop-down always pulls the latest list of available projects. The project on which the query should be executed should be selected.

Location Specify or select a region from the list of suggested locations on which you want to execute BigQuery.

Query

The query that you want to execute on BigQuery for the selected project. For a full list of supported functions and operators for your queries, see Legacy SQL Functions and Operators and Standard SQL Functions and Operators.

Info
We recommend you to add a single query in the SQL Statement field. Make sure that the query conforms to either Standard SQL or Legacy SQL. Use appropriate escape mechanisms for passing special/invalid characters. Backticks ( `) for Standard SQL Square brackets (`[ ]`) in case of Legacy SQL. See Sample Queries for more information.

This setting also supports expressions that can be enabled to parameterize a specific section of the query like table names or columns to be selected.

Standard SQL

Select this checkbox if you want to use the Standard SQL dialect in the Query field. It is crucial that you understand how the Snap interprets the dialect used in the Query field.

Info
Do not select this check box if the query contains `#legacySQL` prefix or uses Legacy SQL dialect.

Default value: Not selected

Destination dataset ID

Dataset ID of the dataset where the destination table has to be created in case of the query returning large query results.

Destination table ID

Table ID of the destination table to write the query results to in case of the query returning large query results.

Action on destination table

This option specifies the action that has to be taken if the destination table already exists. Options available include OVERWRITE, APPEND, and ERROR.

Default value: OVERWRITE

Multiexcerpt include macro

name	Snap Execution
page	SOAP Execute

Multiexcerpt include macro

name	Execution_Detail_Write
page	SOAP Execute

Interpreting the SQL Query Dialect

The Snap determines the SQL dialect used in the query based on the following flags:

Dialect specified as prefix within the Query field (#standardSQL or #legacySQL)
Default Standard SQL check box at account level
Standard SQL check box at Snap level

The prefix specified in the query ignores the other two flags.

When the prefix is not specified,
- The user must select either one of the check boxes at the account level and at the Snap level to specify that the query uses Standard SQL dialect.
  - Else, the query is considered to be written in Legacy SQL.

The following matrix depicts all the possible real-time scenarios for resolving the query dialect:

Prefix in Query	Check box at account level	Check box at Snap level	Query Dialect
Not specified			Legacy SQL
Not specified			Standard SQL
Not specified			Standard SQL
Not specified			Standard SQL
`#legacySQL`			Legacy SQL
`#legacySQL`			Legacy SQL
`#legacySQL`			Legacy SQL
`#legacySQL`			Legacy SQL
`#standardSQL`			Standard SQL
`#standardSQL`			Standard SQL
`#standardSQL`			Standard SQL
`#standardSQL`			Standard SQL

Info

title	For existing Pipelines

If the prefix is defined in the Query field, the query is interpreted accordingly.
- Else, the query is treated as using Legacy SQL dialect.
To mark a query without prefix as using Standard SQL, select the Standard SQL check box at the Snap level.
- To update all Pipelines for an account to use Standard SQL, select the Default Standard SQL checkbox at the account level.

Sample Queries

Here are some SQL statements in each of the two SQL dialects, that the BigQuery Execute Snap can execute:

SQL Operation

Standard SQL

Legacy SQL

Select

Code Block

language	sql

SELECT id, name FROM `project-123.testKamal.TestTablet` 
LIMIT 5000

Code Block

language	sql

SELECT id, name FROM [project-123:testKamal.TestTablet] 
LIMIT 5000

Create (DDL) table with nested array

Code Block

language	sql

CREATE OR REPLACE TABLE `project-123.testKamal.TestTable2` 
( x INT64, y STRUCT< a ARRAY<STRING>, b BOOL > )

Not allowed in Legacy SQL.

Insert (DML)

Code Block

language	sql

INSERT INTO `project-123.testKamal.TestTable2` (x, y) 
VALUES (1, (['1', '2', '3'], true)), (2, (['a', 'b'], 
false))

Not allowed in Legacy SQL.

Row count

Code Block

language	sql

SELECT COUNT(DISTINCT x) FROM `project-
123.testKamal.TestTable2`

Code Block

language	sql

SELECT EXACT_COUNT_DISTINCT(x) FROM [project-
123:testKamal.TestTable2]

Convert an Array into Table rows (Flattening)

Code Block

language	sql

SELECT x, a, y.b as b FROM 
`project-123.testKamal.TestTable2`, UNNEST(y.a) as a

Code Block

language	sql

SELECT x, y.a as a, y.b as b FROM FLATTEN([project-
123:testKamal.TestTable2], y.a)

DROP (DDL)

Code Block

language	sql

DROP TABLE `project-123.testKamal.TestTable2`

Not allowed in Legacy SQL.

After the execution of query, the results are written to the output view. The sample output of Execute Snap looks as follows.

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	Google BigQuery Snap Pack
	Google BigQuery Snap Pack
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Versions Compared

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Key

Settings

Interpreting the SQL Query Dialect

Sample Queries