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  • PowerExchange Adapters for Informatica 10.4.1
  • All Products

Table of Contents

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  1. Abstract
  2. PowerExchange for Amazon Redshift
  3. PowerExchange for Amazon S3
  4. PowerExchange for Cassandra
  5. PowerExchange for Cassandra JDBC
  6. PowerExchange for DataSift
  7. PowerExchange for Facebook
  8. PowerExchange for Google Analytics
  9. PowerExchange for Google BigQuery
  10. PowerExchange for Google Cloud Spanner
  11. PowerExchange for Google Cloud Storage
  12. PowerExchange for Greenplum
  13. PowerExchange for HBase
  14. PowerExchange for HDFS (10.4.1)
  15. PowerExchange for HDFS (10.4.0)
  16. PowerExchange for Hive
  17. PowerExchange for JD Edwards EnterpriseOne
  18. PowerExchange for JDBC V2
  19. PowerExchange for LDAP
  20. PowerExchange for LinkedIn
  21. PowerExchange for MapR-DB
  22. PowerExchange for Microsoft Azure Blob Storage
  23. PowerExchange for Microsoft Azure Cosmos DB SQL API
  24. PowerExchange for Microsoft Azure Data Lake Storage Gen1
  25. PowerExchange for Microsoft Azure Data Lake Storage Gen2
  26. PowerExchange for Microsoft Azure SQL Data Warehouse
  27. PowerExchange for Microsoft Dynamics CRM
  28. PowerExchange for MongoDB
  29. PowerExchange for Netezza
  30. PowerExchange for OData
  31. PowerExchange for Salesforce
  32. PowerExchange for Salesforce Marketing Cloud
  33. PowerExchange for SAP NetWeaver
  34. PowerExchange for Snowflake
  35. PowerExchange for Tableau
  36. PowerExchange for Tableau V3
  37. PowerExchange for Teradata Parallel Transporter API
  38. PowerExchange for Twitter
  39. PowerExchange for Web Content-Kapow Katalyst
  40. Informatica Global Customer Support

PowerExchange Adapters for Informatica Release Notes

PowerExchange Adapters for Informatica Release Notes

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PowerExchange for Google BigQuery Third-Party Known Limitations (10.4.1)

PowerExchange for Google BigQuery Third-Party Known Limitations (10.4.1)

The following table describes third-party known limitations:
Bug
Description
OCON-25412
When you run a Google BigQuery mapping on the Spark engine, the mapping fails when the following conditions are true:
  • You configure a Google BigQuery source and select
    Optimized
     as the
    Spark Mode
    .
  • You configure a Google BigQuery target and select
    Optimized
     as the
    Spark Mode
    .
  • You use any one of the following versions of the Hadoop distribution in the Hadoop environment:
    • Amazon EMR 5.29
    • Amazon EMR 5.26
    • Azure HDInsight 3.6
    • Cloudera CDH 5.16
    • Cloudera CDH 5.13
    • Hortonworks HDP 2.6
    • MapR
Google ticket reference number: 157261131
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