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Set up a sync to Google BigQuery

After setting up your source application in Step 1 of creating a Celigo sync, continue with Step 2: Destination.

  1. Select Google BigQuery from the endpoints listed in Choose destination. (Instructions for other destination endpoints and optimizing ingestion appear in this Help Center category.)
  2. Choose an existing connection to Google BigQuery, or you can click Create connection to define a new resource that you can use here and in other syncs, flows and APIs.
  3. Note: Selecting the same connection used in a flow may slow performance if this sync is scheduled to run at the same time as the flow.

  4. Enter your dataset name to identify the new destination tables that correspond to this dataset. This dataset is for use only with this sync, and you can't change its name after it's created.
  5. GB1.png

Tables created by this sync will be named as follows:

<project>.<dataset>.<table> 

Where...

  • <project> is the default project ID configured on the connection you selected above
  • You entered a <dataset> name above
  • <table> reflects an object/export that you selected or a table name you entered for an export

Then, click Next to save your sync destination and continue with Step 3: Settings.

Edit a sync

After you’ve saved a sync, you can view or modify its settings at any time:

  1. From the Home page, open the integration.
  2. Click the sync name.
  3. Open its Sync details tab.
  4. Click through to the Source, Destination, or Settings step.

Data type mapping

The data types sent to or inferred by Celigo syncs are transferred to Google BigQuery as follows:

Celigo data type
Google BigQuery data type
SHORT INT64
INTEGER INT64
LONG INT64
NUMERIC INT64
NUMERICDECIMAL NUMERIC
NUMERICFLOAT FLOAT64
FLOAT FLOAT64
DOUBLE FLOAT64
NUMBER NUMERIC
DECIMAL NUMERIC
STRING STRING
BINARY BYTES
BOOLEAN BOOL
DATE DATE
TIME TIME
TIMETZ TIME
DATETIMENTZ DATETIME
TIMESTAMP_NTZ DATETIME
DATETIMETZ TIMESTAMP
DATETIMELTZ TIMESTAMP
TIMESTAMP_LTZ TIMESTAMP
TIMESTAMP_TZ TIMESTAMP
ARRAY (default) JSON
ARRAY (primitive element)
ARRAY<element>
ARRAY (arrayDataType = Object) JSON
OBJECT JSON
OBJECT (isJsonStringified = true) STRING
VARIANT JSON
VARIANT (dataType = variant, not stringified) JSON
VARIANT (isJsonStringified = true) STRING
DEFAULT (any unmapped type) STRING
_celigo_extracted_at TIMESTAMP
_celigo_loaded_at TIMESTAMP
_celigo_deleted BOOL

Google BigQuery reserved words

To avoid any conflicts at the destination, Celigo sync automatically handles the use of any Google BigQuery reserved words when creating or updating tables. You may freely use these keywords when defining your source data, although you will see variants in the data warehouse after the sync runs, such as a new table named issue_ instead of the expected (reserved word) ISSUE.

Table and column level reserved words

The following keywords are reserved for both table and column identifiers in Google BigQuery (GoogleSQL):

  • ALL
  • ALTER
  • AND
  • ANY
  • ARRAY
  • AS
  • ASSERT_ROWS_MODIFIED
  • AT
  • BETWEEN
  • BY
  • CASE
  • CAST
  • CHECK
  • COLLATE
  • COLUMN
  • CONNECT
  • CONSTRAINT
  • CONTAINS
  • CREATE
  • CROSS
  • CUBE
  • CURRENT
  • CURRENT_DATE
  • CURRENT_TIME
  • CURRENT_TIMESTAMP
  • CURRENT_USER
  • DEFINE
  • DELETE
  • DISTINCT
  • DROP
  • ELSE
  • ENUM
  • ESCAPE
  • EXCLUDE
  • EXISTS
  • EXTRACT
  • FALSE
  • FETCH
  • FOLLOWING
  • FOR
  • FROM
  • FULL
  • GRANT
  • GROUP
  • GROUPING
  • HASH
  • HAVING
  • IF
  • IGNORE
  • IN
  • INNER
  • INSERT
  • INTERSECT
  • INTERVAL
  • INTO
  • IS
  • JOIN
  • LATERAL
  • LEFT
  • LIKE
  • LIMIT
  • LOCALTIME
  • LOCALTIMESTAMP
  • LOOKUP
  • MERGE
  • NATURAL
  • NEW
  • NO
  • NOT
  • NULL
  • NULLS
  • OF
  • ON
  • OR
  • ORDER
  • OUTER
  • OVER
  • PARTITION
  • PRECEDING
  • PROTO
  • RANGE
  • RECURSIVE
  • RESPECT
  • REVOKE
  • RIGHT
  • ROLLUP
  • ROW
  • ROWS
  • SAMPLE
  • SELECT
  • SET
  • START
  • STRUCT
  • TABLE
  • TABLESAMPLE
  • THEN
  • TO
  • TREAT
  • TRIGGER
  • TRUE
  • TRY_CAST
  • UNBOUNDED
  • UNION
  • UNIQUE
  • UNNEST
  • UPDATE
  • USING
  • VALUES
  • WHEN
  • WHENEVER
  • WHERE
  • WINDOW
  • WITH
  • WITHIN