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Google BigQuery

Google BigQuery is a fully managed cloud data warehouse for analytics. While Google BigQuery works in conjunction with Google Storage for interactive analysis of massively large data sets it can scan TeraBytes in seconds and PetaBytes in minutes.

Type Name

bigquery

Connection Properties

Template name: bigquery

Appropriate translator name: bigquery

Properties:

  • projectId (required)
  • transformQuery (default: TRUE); (obsolete)

  • credentialFactory (default: com.datavirtuality.dv.core.oauth.credential.BigQueryOAuthCredentialFactory)

  • allowLargeResults (obsolete)
  • largeResultsDefaultDataset
  • tableMaxResults
  • fetchSize

  • refreshToken

  • accessToken

  • expirationTimeMilliseconds

  • region

  • authCode

  • redirectUri
  • user-name (required)
  • password (default: empty)
  • ClientId
  • ClientSecret
  • driver (default: bigquery)
  • driver-class (default: com.datavirtuality.jdbc.bq.BQDriver)
  • storageProjectId (default: empty)
  • storageUser (default: empty)
  • storagePassword (default: empty)
  • new-connection-sql
  • check-valid-connection-sql (default: select 1)
  • min-pool-size (default: 2)
  • max-pool-size (default: 70)
  • readTimeout (default: 20000, 0 for an infinite, a negative for the default)
  • connectTimeout (default: 20000, 0 for an infinite, a negative for the default)

readTimeout and connectTimeout connection properties available since v4.6

Here is an example:

SQL 
CALL SYSADMIN.createConnection('bq2','bigquery','projectId=XXXX,user-name=XXXX@developer.gserviceaccount.com,password=$${jboss.server.config.dir}/../deployments/bigquery.p12') ;;
CALL  SYSADMIN.createDatasource('bq2','bigquery','importer.useFullSchemaName=false,importer.useCatalogName=false','supportsNativeQueries=true,uploadMode=CLOUDSTORAGE,bucketName=dv_upload_bucket,useDdl=false') ;;

It is highly recommended to specify a bucketName when creating a BigQuery data source because of the following:

  • a bucket creation limit that can be exceeded while performing multiple data inserts. Please refer to the Google Cloudstorage documentation for detailed information;
  • region mismatch between a BigQuery data set and a temporary bucket which may cause errors while inserting data. Please, refer to the Google BigQuery documentation for more details.

Translator Properties

Translator Properties Shared by All JDBC Connectors

(Properties listed in alphabetical order)

To view the full table, click the expand button in its top right corner


Name

Description

Default value

comparisonStringConversion

Sets a template to convert WHERE clauses on strings

Examples

SQL 
comparisonStringConversion=%s
-- no conversion will be applied

comparisonStringConversion=binary %s
-- WHERE binary someStringExpression LIKE someOtherStringExpression

comparisonStringConversion=(%s COLLATE Latin1_General_CS_AS)
-- WHERE (someStringExpression COLLATE Latin1_General_CS_AS LIKE someOtherStringExpression)


  • MS SQL Server:
    (%s COLLATE Latin1_General_CS_AS)
  • MySQL, SingleStore:
    binary %s
  • Others:
    %s

DatabaseTimeZone

Database time zone, used when fetching date, time, or timestamp values

System default time zone

DatabaseVersion

Specific database version, used to fine-tune pushdown support

Automatically detected by the server through the data source JDBC driver, if possible

forbidNonMatchingNamesOnly considered when importer.tableNamePattern is set. When set to FALSE, allows creation of tables with names that do not match the tableNamePattern. Tables with non-matching names will only be accessible until the server restartsTRUE
ForceQuotedIdentifiers

If TRUE, all identifiers in the final query (that is being generated by a translator to be sent directly to the target DBMS) will be quoted

TRUE

MaxPreparedInsertBatchSize

Maximum size of prepared insert batch

2048

OrderByStringConversion

Sets a template to convert ORDER BY clauses on strings

Examples

SQL 
OrderByStringConversion=%s
-- no conversion will be applied

OrderByStringConversion=(binary %s)
-- ORDER BY (binary someStringExpression)

OrderByStringConversion=cast((%s) as varchar(2000) ccsid 1208)
-- ORDER BY cast((someStringExpression) as varchar(2000) ccsid 1208)
  • DB2 for AS/400:
    cast((%s) as varchar(2000) ccsid 1208)
  • DB2 for zOS:
    cast((%s) as varchar(2000) ccsid ASCII)
  • MS SQL Server:
    (cast(cast(%s as varchar) as varbinary)
  • MySQL, SingleStore:
    (binary %s)
  • PostgreSQL:
    (%s COLLATE \"C\")
  • Others:
    %s
supportsConvertFromClobToString If TRUE, indicates that the translator supports the CONVERT/CAST function from clob to string
  • MySQL, PostgreSQL, Redshift, Greenplum, Oracle, MS SQL Server:
    TRUE 
  • Others:
    FALSE

supportsNativeQueries

Forces a translator to issue a native() system procedure that can be used to pass native queries directly to an underlying DBMS

Example

SQL 
SELECT x.* 
FROM table
  ( 
    CALL "dwh.native"("request" => 'SELECT query, pid, elapsed, substring FROM svl_qlog ORDER BY STARTTIME DESC LIMIT 200') 
  ) w
  , ARRAYTABLE( w.tuple COLUMNS query string, pid integer , elapsed string, "substring" string ) x;

More usage examples

  • MySQL, PostgreSQL, Redshift, Snowflake, Oracle, MS SQL Server; Exasol, Vertica, Bigquery, SingleStore, Azure:
    TRUE
  • Others:
    FALSE
supportsOrderByAlias

If FALSE, the CData Virtuality Server does not generate aliases in the ORDER BY clause.

If TRUE, indicates that the source supports aliases in the ORDER BY clause

  • PostgreSQL:
    TRUE
  • Others:
    • if OrderByStringConversion is not set, same as supportsOrderBy
    • if OrderByStringConversion is set, default for supportsOrderByAlias is  FALSE
supportsOrderByString

If FALSE, the CData Virtuality Server does not push down the ORDER BY clause if it contains at least one expression of string type.

If TRUE, indicates that the source supports strings in the ORDER BY clause

TrimStrings

If TRUE, trims trailing whitespace from fixed-length character strings. Please note that the CData Virtuality Server only has string or varchar type that treats trailing whitespace as meaningful

FALSE

UseBindVariables

if TRUE, indicates that PreparedStatements should be used and that literal values in the source query should be replaced with bind variables. If FALSE, only LOB values will trigger the use of PreparedStatements

TRUE

UseCommentsInSourceQuery

Embeds a / comment / leading comment with session/request id in the source SQL query for informational purposes

FALSE

The names of the translator properties are case-sensitive.

Translator Properties Specific for Google BigQuery

To view the full table, click the expand button in its top right corner

Name

Description

Default value

replaceNullCharsWith

String property. If set, the translator replaces all null characters in strings before executing INSERT / UPDATE with the string specified as the property value. You may specify an empty string as wellSingle space

uploadMode

Values:  CLOUDSTORAGE (default), STREAMING (preview), INSERTS (preview)

  • CLOUDSTORAGE mode uses a Google Cloud Storage bucket to upload data. The bucket can be configured via bucketName or bucketPrefix translator parameters. If no bucketName is specified, the bucket will be created;
  • STREAMING (preview) mode streams data via the BigQuery API;
  • INSERTS (preview) mode uses JDBC prepared statements for inserting data
CLOUDSTORAGE

bucketName

Value: bucket name

Only for the default (CLOUDSTORAGE) upload mode.
Specifies a bucket name to upload data files to. If specified, the specified bucket is assumed to exist (no creation/deletion operations performed). The region specified for the bucket must be the same as the region specified via the region translator property. If no bucketName is specified, a bucket will be created and deleted after the operation is finished.


bucketPrefix

Value: bucket prefix

Only for the default (CLOUDSTORAGE) upload mode.
Specifies a prefix of a bucket name to upload data files to. The name of the bucket created for uploading will start with the specified prefix. The bucket will be deleted after the operation is finished.


folderInBucket

Value: name of a folder in a bucket

Only for the default (CLOUDSTORAGE) upload mode.
Specifies a name of a folder in a bucket to upload data files to. If specified, the specified folder is assumed to exist (no creation/deletion operations performed) within a bukcet. 


useDdl

Value: boolean

If TRUE, creates and drops are performed using JDBC statements instead of API

FALSE

setACLforBucket

If set to TRUE, ACL roles are set for the elements of the bucket used by the data source.

If set to FALSE, only IAM permissions are used. Thus, it should be set when uniform bucket-level access is configured for the bucket

TRUE

folderInBucket translator property available since v4.9

Data Source Properties

Data Source Properties Shared by All JDBC Connectors

(Properties listed in alphabetical order)

To view the full table, click the expand button in its top right corner


Name

Description

Default

importer.autoCorrectColumnNames Replaces . in a column name with _ as the period character is not supported by the CData Virtuality Server in column names TRUE
importer.catalog

Database catalogs to use. Can be used if the db connection property is omitted.

Only for Microsoft SQL Server and Snowflake:

  • Multiple catalogs (multiple databases) usage is supported;
  • '%' as a wildcard is allowed: for example, importer.catalog="foo%" will import foo, foobar, etc.
  • To specify several catalog names or/and patterns, values should be comma-separated and enclosed within double quotes: importer.catalog="schema1,schema2,pattern1%,pattern2%";
  • To use all catalogs, the value should be '%': importer.catalog="%"
  • To escape a wildcard in a catalog name, use the '\' escape character. The value should be as follows: importer.catalog="test\_tables"

Exasol:

SQL 
EXA_DB

All others: empty

importer.defaultSchema
  • Only for data sources that are also supported as Analytical Storage (SQLServer, MySQL, Oracle, PostgreSQL, Redshift);
  • When the property is correctly set, SELECT INTO, CREATE, and DROP TABLE commands are enabled for that data source;
  • Must point to the original schema name in the DBMS (e.g. importer.defaultSchema=public);
  • Needs specifying where tables will be created or dropped in the source DBMS;
  • Not meant to be used with Analytical Storage data source

Please note that writing into a data source is only possible if this parameter is set.

Empty
importer.enableMetadataCache Turns on metadata cache for a single data source even when the global option is turned off. Together with importer.skipMetadataLoadOnStartup=true, it allows using materialized views after server restart when the original source is unavailable
 FALSE
importer.excludeProcedures Case-insensitive regular expression that will exclude a matching fully qualified procedure name from import
Empty
importer.excludeSchemas Comma-separated list of schemas (no % or ? wildcards allowed) to exclude listed schemas from import. A schema specified in defaultSchema or schemaPattern will be imported despite being listed in excludeSchemas. Helps to speed up metadata loading

Oracle:

SQL 
APEX_PUBLIC_USER,
DIP,
FLOWS_040100,
FLOWS_020100,
FLOWS_FILES,
MDDATA,
ORACLE_OCM,
SPATIAL_CSW_ADMIN_USR,
SPATIAL_WFS_ADMIN_USR,
XS$NULL,
BI,
HR,
OE,
PM,
IX,
SH,
SYS,
SYSTEM,
MDSYS,
CTXSYS

All others: empty

importer.excludeTables

Case-insensitive regular expression that will exclude a matching fully qualified table name from import. Does not speed up metadata loading. Here are some examples:

1. Excluding all tables in the (source) schemas sys and INFORMATION_SCHEMA:

SQL 
importer.excludeTables=(.*[.]sys[.].*|.*[.]INFORMATION_SCHEMA[.].*)

2. Excluding all tables except the ones starting with "public.br" and "public.mk" using a negative lookahead: 

SQL 
importer.excludeTables=(?!public\.(br|mk)).*

3. Excluding "tablename11" from the list ["tablename1", "tablename11", "company", "companies"]:

SQL 
importer.excludeTables=.*\.(?!\btablename1\b|\bcompan).*
  • ".*\." will match the schema portion of the table name;
  • "\b" is a word boundary. It is used to define the boundary between text characters and non-character text;
  • "\btablename1\b" will only match tablename1 and not tablename11 because of the use of "\b";
  • "\bcompan" will match "company" and "companies" because we did not use "\b" at the end to delimit a word boundary;
  • ".*" at the end is necessary to match the trailing characters after the name

Empty

importer.fetchSize

Fetch size assigned to a resultset on loading metadata

No default value

importer.importApproximateIndexes

If set to TRUE, imports approximate index information

TRUE

importer.importIndexes If set to TRUE, imports index/unique key/cardinality information FALSE
importer.importKeys If set to TRUE, imports primary and foreign keys FALSE

importer.importProcedures

If set to TRUE, imports procedures and procedure columns. Overloaded procedures can be imported with an additional option useProcedureSpecificName.

Please note that it is currently not possible to import procedures which use the same name for more than one parameter (e.g. same name for IN and OUT parameters). Such procedures can be excluded from import with the parameter excludeProcedures.
Please note that it is not always possible to import procedure result set columns due to database limitations

FALSE

TRUE only for CData connector

importer.loadColumnsTableByTableSet to TRUE to force table by table metadata processingFALSE/TRUE only for Netsuite and SAP Advantage Database Server
importer.loadMetadataWithJdbc If set to TRUE, turns off all custom metadata load ways FALSE
importer.loadSourceSystemFunctionsIf set to TRUE, data source-specific functions are loaded. Supported for Microsoft SQL Server and AzureFALSE
importer.procedureNamePattern Procedure(s) to import. If omitted, all procedures will be imported. % as a wildcard is allowed: for example, importer.procedureNamePattern=foo% will import foo , foobar, etc. W orks only in combination with importProcedures Empty

importer.quoteNameInSource

If set to FALSE, directs the Data Virtuality Server to create source queries using unquoted identifiers

TRUE

importer.renameDuplicateColumns If set to TRUE,  renames duplicate columns caused by either mixed case collisions or autoCorrectColumnNames replacing . with _. The suffix _n where n is an integer will be added to make the name unique TRUE
importer.renameDuplicateTables If set to TRUE, renames duplicate tables caused by mixed case collisions. The suffix _n where n is an integer will be added to make the name unique TRUE
importer.replaceSpecSymbsInColNamesIf set to TRUE, replaces all special symbols (any symbols not in the ^A-Za-z0-9_ sequence) to the _ symbol in column names of tables FALSE / TRUE only for BigQuery
importer.schemaPattern Schema(s) to import. If omitted or has "" value, all schemas will be imported. % as wildcard is allowed: for example, importer.schemaPattern=foo% will import foo, foobar, etc. To specify several schema names or/and patterns, values should be comma-separated and enclosed within double quotes: importer.schemaPattern="schema1,schema2,pattern1%,pattern2%". For proper escaping of special characters depending on the type of data source, check Escaping special characters in schema names or use wildcards instead: "[schema_name]" can be rewritten as "%schema%name%". Helps to speed up metadata loadingEmpty
importer.skipMetadataLoadOnStartup

If set to TRUE, allows skipping metadata loading on server startup if there's cached metadata for the data source. . Together with importer.enableMetadataCache=true, it allows using materialized views after server restart when the original source is unavailable

 FALSE
importer.tableNamePattern Table(s) to import. If omitted, all tables will be imported. % as a wildcard is allowed: for example, importer.tableNamePattern=foo% will import foo, foobar, etcEmpty
importer.tableTypes

Comma-separated list (without spaces) of table types to import. Available types depend on the DBMS. Usual format: "TABLE,VIEW".

Other typical types are "SYSTEM TABLE", "GLOBAL TEMPORARY", "LOCAL TEMPORARY", "ALIAS", "SYNONYM"

Empty
importer.useCatalogName If set to TRUE, uses any non-null/non-empty catalogue name as part of the name in source, e.g. "catalogue"."table"."column", and in the CData Virtuality Server runtime name if useFullSchemaName is TRUE. If set to FALSE, will not use the catalogue name in either the name in source or the CData Virtuality Server runtime name. Should be set to FALSE for sources that do not fully support a catalogue concept, but return a non-null catalogue name in their metadata - such as HSQL TRUE / FALSE only for Hive and EXASOL
importer.useFullSchemaName

If set to FALSE, directs the importer to drop the source catalogue/schema from the CData Virtuality Server object name so that the CData Virtuality Server fully qualified name will be in the form of <model name>.<table name>.

Please note that this may lead to objects with duplicate names when importing from multiple schemas, which results in an exception

 TRUE
importer.useProcedureSpecificName If set to TRUE, allows the import of overloaded procedures (which will normally result in a duplicate procedure error) by using the unique procedure specific name in the CData Virtuality Server. This option will only work with JDBC 4.0 compatible drivers that report specific names FALSE
importer.widenUnsignedTypes If set to TRUE, converts unsigned types to the next widest type. For example, SQL Server reports tinyint as an unsigned type. With this option enabled, tinyint would be imported as a short instead of a byte TRUE
The names of the data source properties are case-sensitive.

Escaping wildcards in importer.catalog available since v4.0.8

Default values importer.catalog='EXA_DB' and importer.useCatalogName=FALSE available since v4.4

importer.loadSourceSystemFunctions is available since v4.6

importer.importProcedures set to TRUE by default for CData connector since v4.7

Creating/Dropping Tables and Inserting Data

In order to create/drop tables and insert data into a BigQeury data source, the importer.defaultSchema  data source property should be set to the name of the target dataset. Here is an example:

SQL 
CALL SYSADMIN.createConnection(name => 'bq', jbossCliTemplateName => 'bigquery', connectionOrResourceAdapterProperties => 'projectId=XXXX,user-name=XXXX-ZZZZ@developer.gserviceaccount.com,password=PATH_TO_KEY_FILE') ;;
CALL SYSADMIN.createDatasource(name => 'bq', translator => 'bigquery', modelProperties => 'importer.useCatalogName=false,importer.defaultSchema=TARGET_DATA_SET,importer.schemaPattern=SCHEMA_PATTERN_INCLUDING_TARGET_DATASET,importer.useFullSchemaName=false') ;;

Segmenting with Partitioned Tables

The BigQuery partitioning functionality is supported in both API and DDL (useDdl=TRUE) modes.

Partitioning is supported via the OPTIONS clause. 

Types of Partitioning

Integer range partitioning

You can partition a table based on ranges of values in a specific INTEGER column. 

Time-unit column partitioning

You can partition a table on a DATE or TIMESTAMP column in the table. 

For the TIMESTAMP column, the partitions can have either hourly, daily, monthly, or yearly granularity. For DATE columns, the partitions can have daily, monthly, or yearly granularity. Partitions boundaries are based on UTC time.

Ingestion time partitioning

Valid only for DDL mode.

An ingestion-time partitioned table has a pseudocolumn named _PARTITIONTIME. The value of this column is the ingestion time for each row, truncated to the partition boundary (such as hourly or daily). Instead of using _PARTITIONTIME, you can also use _PARTITIONDATE. The _PARTITIONDATE pseudocolumn contains the UTC date corresponding to the value in the _PARTITIONTIME pseudocolumn.

You can choose hourly, daily, monthly, or yearly granularity for the partitions. 

Partitioning Options

partition_expiration_days 

When you create a table partitioned by ingestion time or time-unit column, you can specify a partition expiration. This setting specifies how long BigQuery keeps the data in each partition. The setting applies to all partitions in the table, but is calculated independently for each partition based on the partition time.

Accepts FLOAT values.

require_partition_filter

Specifies whether queries on this table must include a a predicate filter that filters on the partitioning column. The default value is FALSE.

partition_expression

Partition_expression is an expression that determines how to partition the table. The partition expression can contain the following values:

partition_expression descriptionpartitioning typevalid for mode
_PARTITIONDATEPartition by ingestion time with daily partitions

Ingestion time

DDL
DATE(_PARTITIONTIME)Equivalent to _PARTITIONDATE

Ingestion time

DDL

<date_column>

Partition by the DATE column with daily partitions

Time-unit column

API/DDL

DATE( <timestamp_column> ) 

Partition by the TIMESTAMP column with daily partitions.Time-unit columnAPI/DDL

DATETIME_TRUNC(<timestamp_column>, { DAY | HOUR | MONTH | YEAR }) 

Partition by the TIMESTAMP column with the specified partitioning type.Time-unit columnAPI/DDL

TIMESTAMP_TRUNC(<timestamp_column>, { DAY | HOUR | MONTH | YEAR })

Partition by the TIMESTAMP column with the specified partitioning type.Time-unit columnDDL
TIMESTAMP_TRUNC(_PARTITIONTIME, { DAY | HOUR | MONTH | YEAR })Partition by ingestion time with the specified partitioning type.Ingestion timeDDL

DATE_TRUNC(<date_column>, { MONTH | YEAR }) 

Partition by the DATE column with the specified partitioning type.Time-unit columnAPI/DDL

RANGE_BUCKET(<int64_column>, GENERATE_ARRAY(<start>, <end>[, <interval>]))

Partition by an integer column with the specified range, where:

    • start is the start of range partitioning, inclusive.
    • end is the end of range partitioning, exclusive.
    • interval is the width of each range within the partition. Defaults to 1.

Integer range

API/DDL

Examples

Partitioning by DATE column with daily granularity, keeping data for 3 days in partition and required filter that filters on the partitioning column for querying from table which means that the select query should contains where clause with DATE column.

SQL 
CREATE TABLE bigquery.partition1 (i INTEGER, d DATE, s STRING) OPTIONS (partition_by 'd',partition_expiration_days '3', require_partition_filter 'true') ;;

Creating a table partitioned on a timestamp range with monthly granularity:

SQL 
CREATE TABLE bigquery_ddl.partition_ddl_date (i integer, d timestamp, s string) OPTIONS (partition_by 'DATE_TRUNC(d, MONTH)') ;;

Creating a table partitioned on integer range required filter that filters on the partitioning column for querying from table which means that the select query should contains where clause with INTEGER column:

SQL 
CREATE TABLE bigquery_ddl.partition_ddl_integer (i integer, d timestamp, s string) OPTIONS (partition_by 'RANGE_BUCKET(i, GENERATE_ARRAY(0, 100, 10))', require_partition_filter 'true') ;;

Partitioning options and integer-range, date-unit partitioning for API mode are available since v4.10

Clustering

Clustering is supported via the OPTIONS clause:

SQL 
CREATE TABLE bigquery.cluster (i integer, d date, ts timestamp, s string, b boolean) OPTIONS (cluster_by 'i,d,ts,s') ;;

Configuring 3-legged OAuth for BigQuery

To set up 3-legged OAuth with BigQuery, follow these steps:

1. Log in to the Developer Console for your BigQuery project.

2. Generate new OAuth2 credentials (a pair of CLIENT_ID and CLIENT_SECRET keys).

3. Substitute CLIENT_ID in the link below with your CLIENT_ID and follow this link in the browser:

https: //accounts.google.com/o/oauth2/auth?scope=https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fbigquery&access_type=offline&state=security_token&response_type=code&client_id=CLIENT_ID&approval_prompt=force&redirect_uri=http%3A%2F%2Flocalhost%3A9000%2Fredirect.html%3Fto%3Dconnect/bigquery/oauth

4. Choose 'Allow' to provide access:

5. You will be redirected to a non-existent page, which is correct. Copy the page URL to obtain the code:

(warning) The OAuth code is only valid for 10 minutes

http: //localhost:9000/redirect.html?to=connect/bigquery/oauth&state=security_token&code=4/cwHserUpJwJSbKWQX-1Ua-cw5xWtdJPEDBx4nfbRmJ9F0wW2NVlLEhE8umS9bE6cdXas0IK9FZfirA02ZYDeTTw&scope=https://www.googleapis.com/auth/bigquery


6. Create a data source using the CLIENT_ID and CLIENT_SECRET obtained in step 3, AUTH_CODE obtained in step 5, and PROJECT_ID of your BigQuery project. The redirectUrl should be the same as in steps 3 and 5:

SQL 
CALL SYSADMIN.createConnection('bq3legged','bigquery','authType=OAUTH,
projectId=PROJECT_ID ,
authCode=AUTH_CODE ,
redirectUri=http%3A%2F%2Flocalhost%3A9000%2Fredirect.html%3Fto%3Dconnect/bigquery/oauth,
user-name=CLIENT_ID,
password=CLIENT_SECRET') ;;
CALL SYSADMIN.createDatasource('bq3legged','bigquery','importer.schemaPattern=bq_schema_pattern,importer.defaultSchema=bq_schema,
	importer.useFullSchemaName=false,importer.useCatalogName=false','supportsNativeQueries=true') ;;

See Also

Partitioning Tables in BigQuery to learn how to convert a non-partitioned table into a partitioned one for improved query performance


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