Table of Contents

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  1. Preface
  2. Part 1: Getting Started with Snowflake Data Cloud Connector
  3. Part 2: Data Integration with Snowflake Data Cloud Connector
  4. Part 3: SQL ELT with Snowflake Data Cloud Connector
  5. Appendix A: Data type reference
  6. Appendix B: Additional runtime configurations
  7. Appendix C: Upgrading to Snowflake Data Cloud Connector

Snowflake Data Cloud Connector

Snowflake Data Cloud Connector

Rules and guidelines for data types

Rules and guidelines for data types

When you read or write data, some differences in processing and configuration apply for certain data types.

Mappings

Consider the following rules and guidelines for mappings:
  • You can read or write data of Binary data type that is in Hexadecimal format.
  • The agent reads or writes the maximum float value
    1.7976931348623158e+308
    as infinity.
  • You can use the following formats to specify filter values of the Datetime data type:
    • YYYY-MM-DD HH24:MI:SS
    • YYYY/MM/DD HH24:MI:SS
    • MM/DD/YYYY HH24:MI:SS
  • If a Snowflake Cloud Data lookup object contains fields with the String data type of maximum or default precision and the row size exceeds the maximum row size, the task fails.
  • The performance of a write operation slows down if the data contains the Date fields.
  • A task that captures changed data from a CDC source fails when the Snowflake target contains a repeated column of the Record data type.
  • When you handle dynamic schemas in mappings, the following updates are not applicable:
    • Schema updates to the Timestamp and Date data types.
    • Schema updates that involve a decrease in the precision of the Varchar data type.

Mappings in advanced mode

Consider the following rules and guidelines for mappings in advanced mode:
  • When you read Time data types, you must map the Time to Timestamp in the SQL override for column of type Time. For example, see the sample SQL override query:
    SELECT "C1_DATE", to_timestamp (to_char("C2_TIME_3" , 'HH24:MI:SS.FF'), 'HH24:MI:SS.FF') AS "C2_TIME_3", to_timestamp (to_char("C3_TIME_5" , 'HH24:MI:SS.FF'), 'HH24:MI:SS.FF') AS "C3_TIME_5", to_timestamp (to_char("C4_TIME" , 'HH24:MI:SS.FF'), 'HH24:MI:SS.FF') AS "C4_TIME" FROM "SALES"."SF_DEV"."SRC_DATE_TIME"
  • When you handle dynamic schemas, the following updates are not applicable:
    • Schema updates that involve a decrease in the precision of the Varchar data type.
    • Schema updates to the Timestamp and Date data types.
    • When you use the alter and apply changes option to write to the Snowflake target, Data Integration ignores the changes made to the Timestampntz, Datetime, Timestamptz, Timestampltz, and Boolean data types from the source schema.

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