We have a Data Connector to a Postgres database (AWS Aurora). The connector can browse the table space and read data from the tables. However, when we try export a data set through the connector we get a failure.
Steps to perform export:
Navigate to Library.
Select EXPORT from the data set.
Select the configured Postgres data connector.
Browse the table space to the location "demand_planning/public". No tables are listed.
Click the SELECT button.
For the name, enter "DataQualityResults". This is the name of an existing table under "demand_planning/public".
The export fails with the following error.
Reason: Batch entry 0 INSERT INTO "demand_planning"."public"."DataQualityResults" ("CLIENT", "RECORD_TYPE", "ITEM_DESCRIPTION", "SALES_UOM", "ALL_EXCEPTIONS", "EXCEPTION_DESCRIPTION", "TIMESTAMP", "ITEM_NUMBER", "UA_ITEM_DESCRIPTION", "UNIT_OF_MEASURE_CONVERSION", "ALTERNATE_UNIT_OF_MEASURE", "ALT_UOM_QUANTITY", "UNIT_OF_MEASURE (UOM)", "WEEK_STARTING_DATE") VALUES ('Wings','SALES_HISTORY',NULL,'EA','SE008|SE003','Missing Item Number In Sales History|Se003|||||','2019-10-01',NULL,'Classic Buffalo',NULL,NULL,NULL,'EA','2019-3-17 17:0:0.000000 -7:0:0') was aborted. Call getNextException to see the cause.
If we enter a new unique name (that isn't an existing table), the export succeeds.
We are using the master user and password for the database, so it cannot be a database permissions error.
When attempting to export data into an existing database table, you have to make sure that the column names of the new dataset exactly match the the existing table. Can you verify that the dataset and table columns match?
If they don't match, you can rename the columns in a Project to match the table structure and attempt to export again.