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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
  15. PowerExchange for Hive
  16. PowerExchange for JD Edwards EnterpriseOne
  17. PowerExchange for JDBC V2
  18. PowerExchange for LDAP
  19. PowerExchange for LinkedIn
  20. PowerExchange for MapR-DB
  21. PowerExchange for Microsoft Azure Blob Storage
  22. PowerExchange for Microsoft Azure Cosmos DB SQL API
  23. PowerExchange for Microsoft Azure Data Lake Storage Gen1
  24. PowerExchange for Microsoft Azure Data Lake Storage Gen2
  25. PowerExchange for Microsoft Azure SQL Data Warehouse
  26. PowerExchange for Microsoft Dynamics CRM
  27. PowerExchange for MongoDB
  28. PowerExchange for Netezza
  29. PowerExchange for OData
  30. PowerExchange for Salesforce
  31. PowerExchange for Salesforce Marketing Cloud
  32. PowerExchange for SAP NetWeaver
  33. PowerExchange for Snowflake
  34. PowerExchange for Tableau
  35. PowerExchange for Tableau V3
  36. PowerExchange for Teradata Parallel Transporter API
  37. PowerExchange for Twitter
  38. PowerExchange for Web Content-Kapow Katalyst
  39. Informatica Global Customer Support

PowerExchange Adapters for Informatica Release Notes (10.4.1.3)

PowerExchange Adapters for Informatica Release Notes (10.4.1.3)

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

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

The following table describes third-party known issues:
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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