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  • Common Content for Data Engineering 10.5.3
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Table of Contents

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  1. Preface
  2. Command Line Programs and Utilities
  3. Installing and Configuring Command Line Utilities
  4. Using the Command Line Programs
  5. Environment Variables for Command Line Programs
  6. Using infacmd
  7. infacmd as Command Reference
  8. infacmd aud Command Reference
  9. infacmd autotune Command Reference
  10. Infacmd bg Command Reference
  11. infacmd ccps Command Reference
  12. infacmd cluster Command Reference
  13. infacmd cms Command Reference
  14. infacmd dis Command Reference
  15. Infacmd dis Queries
  16. infacmd dp Command Reference
  17. infacmd idp Command Reference
  18. infacmd edp Command Reference
  19. Infacmd es Command Reference
  20. infacmd ics Command Reference
  21. infacmd ipc Command Reference
  22. infacmd isp Command Reference
  23. infacmd ldm Command Reference
  24. infacmd mas Command Reference
  25. infacmd mi Command Reference
  26. infacmd mrs Command Reference
  27. infacmd ms Command Reference
  28. infacmd oie Command Reference
  29. infacmd ps Command Reference
  30. infacmd pwx Command Reference
  31. infacmd roh Command Reference
  32. infacmd rms Command Reference
  33. infacmd rtm Command Reference
  34. infacmd sch Command Reference
  35. infacmd search Command Reference
  36. infacmd sql Command Reference
  37. infacmd tdm Command Reference
  38. infacmd tools Command Reference
  39. infacmd wfs Command Reference
  40. infacmd ws Command Reference
  41. infacmd xrf Command Reference
  42. infacmd Control Files
  43. infasetup Command Reference
  44. pmcmd Command Reference
  45. pmrep Command Reference
  46. Working with filemanager
  47. Working with pmrep Files

Command Reference

Command Reference

Back Next

Google BigQuery Connection Options

Google BigQuery Connection Options

Use connection options to define the Google BigQuery connection.
Enter connection options in the following format: 
 ... -o option_name=value option_name=value ...
Separate multiple options with a space. To enter a value that contains a space or other non-alphanumeric character, enclose the value in quotation marks.
For example, 
./infacmd.sh createconnection -dn Domain_Adapters_1041_Uni -un Administrator -pd Administrator -cn GBQ_BDM -ct BIGQUERY -o "CLIENTEMAIL='ics-test@api-project-80697026669.iam.gserviceaccount.com' PRIVATEKEY='-----BEGIN PRIVATE KEY-----\nMIIgfdzhgy74587igu787tio9QEFAASCBKgwggSkAgEAAoIBAQCy+2Dbh\n-----END PRIVATE KEY-----\n' PROJECTID=api-project-86699686669 CONNECTORTYPE=Simple SCHEMALOCATION='gs://0_europe-west6_region' STORAGEPATH='gs://0_europe-west6_region' DATASETNAMEFORCUSTOMQUERY='europe_west6' REGIONID='europe-west6'" ;
The following table describes Google BigQuery connection options for infacmd isp CreateConnection and UpdateConnection commands:
Property
Description
CLIENTEMAIL
Required. Specifies the client_email value present in the JSON file that you download after you create a service account in Google BigQuery.
PRIVATEKEY
Required. Specifies the private_key value present in the JSON file that you download after you create a service account in Google BigQuery.
Connection Mode
CONNECTORTYPE
Required. The connection mode that you want to use to read data from or write data to Google BigQuery.
Enter one of the following connection modes:
  • Simple. Flattens each field within the Record data type field as a separate field in the mapping.
  • Hybrid. Displays all the top-level fields in the Google BigQuery table including Record data type fields. PowerExchange for Google BigQuery displays the top-level Record data type field as a single field of the String data type in the mapping.
  • Complex. Displays all the columns in the Google BigQuery table as a single field of the String data type in the mapping.
Default is Simple.
Schema Definition File Path
SCHEMALOCATION
Required. Specifies a directory on the client machine where the PowerExchange for Google BigQuery must create a JSON file with the sample schema of the Google BigQuery table. The JSON file name is the same as the Google BigQuery table name.
Alternatively, you can specify a storage path in Google Cloud Storage where the PowerExchange for Google BigQuery must create a JSON file with the sample schema of the Google BigQuery table. You can download the JSON file from the specified storage path in Google Cloud Storage to a local machine.
PROJECTID
Required. Specifies the project_id value present in the JSON file that you download after you create a service account in Google BigQuery.
If you have created multiple projects with the same service account, enter the ID of the project that contains the dataset that you want to connect to.
STORAGEPATH
Required when you read or write large volumes of data.
Path in Google Cloud Storage where PowerExchange for Google BigQuery creates a local stage file to store the data temporarily.
You can either enter the bucket name or the bucket name and folder name.
For example, enter
gs://<bucket_name>
 or
gs://<bucket_name>/<folder_name>
REGIONID
The region name where the Google BigQuery dataset resides.
For example, if you want to connect to a Google BigQuery dataset that resides in Las Vegas region, specify
us-west4
 as the
Region ID
.
In the
Storage Path
 connection property, ensure that you specify a bucket name or the bucket name and folder name that resides in the same region as the dataset in Google BigQuery.
For more information about the regions supported by Google BigQuery, see the following Google BigQuery documentation:https://cloud.google.com/bigquery/docs/locations
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