Google BigQuery Mapping Columns
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Google BigQuery Mapping Columns

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Article summary

Type Mapping

While extracting your data, we match BigQuery data types to Rivery data types. If a data type isn't supported, we will automatically map it as a String type.

The mapping of BigQuery data types to Rivery-compatible types is shown in the table below:

Rivery TypeBigQuery Type
STRING
STRING
INTERGERINTERGER
FLOATFLOAT
BOOLEAN
BOOLEAN
TIMESTAMPTIMESTAMP
DATEDATE
TIMETIME
RECORD
STRING
SHORTDECIMAL
(up to 9 decimal places)
NUMERIC
LONGDECIMAL
(more than 9 decimal places)
BIGNUMERIC

Scenarios of Data Type Conflicts

In instances where a datatype mismatch occurs, for example, when the datatype of an existing column in the source table is modified, the datatype of the corresponding column in the target table will be determined based on certain defined rules, thereby resolving the conflict. These rules ensure that the most comprehensive data type is chosen to maintain data integrity and avoid loss of information.

Examples of Data Type Conflicts

The table below outlines various scenarios of data type conflicts and the resolution rules. The Inferred Type column represents the chosen data type in the target table when there's a conflict.

Conflicting TypesInferred TypeExample Scenario
TIMESTAMP vs. DATETIMESTAMPIf a column in the source, initially of TIMESTAMP type, is changed to DATE, it will be converted into TIMESTAMP in the target.
SMALLINT vs. BOOLEANSMALLINTA conflict between SMALLINT and BOOLEAN types in the source column will lead to the target column adopting the SMALLINT type.
INTEGER vs. (SMALLINT / BOOLEAN)INTEGERIf an INTEGER is updated to SMALLINT or BOOLEAN in the source, it will be promoted to INTEGER in the target.
BIGINT vs. (INTEGER / SMALLINT / BOOLEAN)BIGINTIf a column of BIGINT type is changed to SMALLINT, BOOLEAN, or INTEGER in the source, it will be elevated to BIGINT in the target.
DECIMAL vs. (INTEGER / BIGINT / SMALLINT / BOOLEAN)DECIMALA column that is INTEGER or DECIMAL in the source will be transformed into DECIMAL.
DOUBLE PRECISION vs. (INTEGER / BIGINT / SMALLINT / BOOLEAN)DOUBLE PRECISIONIf there is a conflict between DOUBLE PRECISION and SMALLINT in the source column, the target column will adopt DOUBLE PRECISION.
REAL vs. (DOUBLE PRECISION / DECIMAL / INTEGER / BIGINT / SMALLINT / BOOLEAN)REALIf a column of DOUBLE PRECISION type is altered to REAL type in the source, it will remain as REAL in the target.
FLOAT vs. (INTEGER / BIGINT / SMALLINT / DECIMAL / REAL / DOUBLE PRECISION / BOOLEAN)FLOATA source column initially of FLOAT type that is updated to INTEGER will remain as FLOAT in the target.
VARCHAR vs. ALL DATATYPESVARCHARIf a column in the source was VARCHAR type and has been updated to INTEGER type, the target column will still retain the VARCHAR type.
OBJECT vs. ALL DATATYPESOBJECTIf a source column is initially set as OBJECT type and later changed to DATE or INTEGER, it will still be treated as OBJECT type in the target.

Please Note:

VARCHAR and OBJECT have higher priority and will override other data types in conflicts.


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