In this reference:

Common loading errors

The following errors are applicable to multiple or all destinations:

Column name exceeds destination limit 

Column name [COLUMN] is too long for [DESTINATION]
Applicable to

All destinations
Level Warning
Category

Destination object naming
Potential cause(s)

A column name contains more characters than allowed by the destination.
Suggested action(s)
  1. If possible, change the column name in the source to be less than the destination’s limit for column names, or
  2. De-select the column in Stitch

If neither solution is feasible, you may need to select a destination with a higher character limit for column names. Refer to the table below for each destination’s column name limits:

Destination Version Limit
Amazon Redshift v2 115 characters
Amazon S3 v1 None
data.world v1 None
Databricks Delta Lake (AWS) v1 122 characters
Google BigQuery v1 128 characters
Google BigQuery v2 128 characters
Microsoft Azure Synapse Analytics v1 128 characters
Microsoft SQL Server v1 128 characters
MySQL v1 64 characters
Panoply v2 115 characters
PostgreSQL v1 59 characters
Snowflake v1 251 characters

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Table or column contains reserved words 

column names from client should not include reserved datatype suffix on [COLUMN_NAME]
Applicable to

All destinations
Level Warning
Category

Stitch object naming
Potential cause(s)

A table or column contains reserved words.
Suggested action(s)

Remove the reserved words by re-naming the table or column in the source.

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Decimal out of range 

decimal out of range for [DESTINATION] on [DECIMAL]
Applicable to

All destinations
Level Warning
Category

Destination data type limits
Potential cause(s)

Decimal data exceeds the destination’s allowed range.
Suggested action(s)

Remove offending values in the source, or change them to be within the allowed range for the destination type:

Destination Version Range
Amazon Redshift v2

Precision must be between 1 and 38; scale must be between 0 and the precision value
Databricks Delta Lake (AWS) v1
Google BigQuery v1

-99999999999999999999999999999.999999999 to 99999999999999999999999999999.999999999
Google BigQuery v2

-99999999999999999999999999999.999999999 to 99999999999999999999999999999.999999999
Microsoft Azure Synapse Analytics v1

Precision must be between 1 and 38; scale must be between 0 and the precision value
Microsoft SQL Server v1

-99999999999999999999999999999999.999999 to 99999999999999999999999999999999.999999
MySQL v1

-99999999999999999999999999999999.999999M to 99999999999999999999999999999999.999999M
Panoply v2

Precision must be between 1 and 38; scale must be between 0 and the precision value
PostgreSQL v1

Up to 131,072 digits before the decimal; up to 16,383 digits after
Snowflake v1

Precision must be between 1 and 38; scale must be between 0 and the precision value

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Table contains too many columns 

ERROR: too many columns
Applicable to

All destinations
Level Warning
Category

Destination object limits
Potential cause(s)

A table contains more columns than the destination allows.
Suggested action(s)

De-select columns in Stitch to allow data to continue loading into the destination table.

Refer to the table below for each destination’s columns per table limit:

Destination Version Limit
Amazon Redshift v2 1,600
Amazon S3 v1 None
data.world v1 None
Databricks Delta Lake (AWS) v1 None
Google BigQuery v1 10,000
Google BigQuery v2 10,000
Microsoft Azure Synapse Analytics v1 1,024
Microsoft SQL Server v1 1,024
MySQL v1 1017
Panoply v2 1,600
PostgreSQL v1 250-1,600
Snowflake v1 None

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Column name collision 

Field collision on [COLUMN_NAME]
Applicable to

All destinations
Level Warning
Category

Destination object naming
Potential cause(s)

Two columns are replicated that canonicalize to the same name.

For example: In Amazon Redshift, Stitch lowercases column names cUsTomErId and customerid would can
Suggested action(s)

If possible, re-name one of the columns in the source so that both column names will be unique when replicated to the destination.

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Integer out of range 

integer out of range for [DESTINATION] on [INTEGER]
Applicable to

All destinations
Level Warning
Category

Destination data type limits
Potential cause(s)

Integer data exceeds the destination’s allowed range.
Suggested action(s)

Remove offending values in the source, or change them to be within the allowed range for the destination type:

Destination Version Range
Amazon Redshift v2

-9223372036854775808 to 9223372036854775807
Databricks Delta Lake (AWS) v1
Google BigQuery v1

-9,223,372,036,854,775,808 to 9,223,372,036,854,775,807
Google BigQuery v2

-9,223,372,036,854,775,808 to 9,223,372,036,854,775,807
Microsoft Azure Synapse Analytics v1

-2^63 (-9,223,372,036,854,775,808) to 2^63-1 (9,223,372,036,854,775,807)
Microsoft SQL Server v1

-2^31 (-2,147,483,648) to 2^31-1 (2,147,483,647)
MySQL v1

-2147483648 to 2147483647
Panoply v2

-9223372036854775808 to 9223372036854775807
PostgreSQL v1

-2147483648 to +2147483647
Snowflake v1

Limited to 38 digits of scale

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Table name exceeds destination limit 

Table name [TABLE] is too long for [DESTINATION]
Applicable to

All destinations
Level Warning
Category

Destination object naming
Potential cause(s)

A table name contains more characters than allowed by the destination.
Suggested action(s)
  1. If possible, change the table name in the source to be less than the destination’s limit for table names, or
  2. De-select the table in Stitch

If neither solution is feasible, you may need to select a destination with a higher character limit for table names. Refer to the table below for each destination’s table name limits:

Destination Version Limit
Amazon Redshift v2 127 characters
Amazon S3 v1 1,024 bytes
data.world v1 None
Databricks Delta Lake (AWS) v1 78 characters
Google BigQuery v1 1,024 characters
Google BigQuery v2 1,024 characters
Microsoft Azure Synapse Analytics v1 112 characters
Microsoft SQL Server v1 113 characters
MySQL v1 60 characters
Panoply v2 127 characters
PostgreSQL v1 63 characters
Snowflake v1 255 characters

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Timestamp out of range 

timestamp out of range for [DESTINATION] on [TIMESTAMP]
Applicable to

All destinations
Level Warning
Category

Destination data type limits
Potential cause(s)

Timestamp data exceeds the destination’s allowed range.
Suggested action(s)

Remove offending values in the source, or change them to be within the allowed range for the destination type:

Destination Version Range
Amazon Redshift v2

4713 BC to 294276 AD
Databricks Delta Lake (AWS) v1

Timestamps before 1900-01-01T00:00:00Z are not supported.
Google BigQuery v1

0001-01-01 00:00:00 to 9999-12-31 23:59:59.999999 UTC
Google BigQuery v2

0001-01-01 00:00:00 to 9999-12-31 23:59:59.999999 UTC
Microsoft Azure Synapse Analytics v1

Dates: 0001-01-01/January 1, 0001 AD, through 9999-12-31/December 31, 9999 AD; Time: 00:00:00 through 23:59:59.997
Microsoft SQL Server v1

Date: 0001-01-01 through 9999-12-31; Time: 00:00:00 through 23:59:59.999
MySQL v1

1000-01-01 to 9999-12-31
Panoply v2

4713 BC to 294276 AD
PostgreSQL v1

4713 BC to 294276 AD
Snowflake v1

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Amazon Redshift and Panoply loading errors

Cannot create new schema 

Encountered error while attempting to create new schema.
Applicable to

Amazon Redshift destinations
Level Critical
Category

Database user privileges
Potential cause(s)

Stitch is unable to create or load data into a schema in your destination. This is usually due to insufficient database user privileges.
Suggested action(s)

Verify that the database user authorizing the connection has all the required privileges as outlined in the Amazon Redshift setup instructions.

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Dependent views 

ERROR: cannot drop table [SCHEMA_NAME].[TABLE_NAME] column type because other objects depend on it
Hint: Use DROP ... CASCADE to drop the dependent objects too.
Applicable to

Amazon Redshift destinations
Level Critical
Category

Dependent views
Potential cause(s)

Stitch is attempting to widen a VARCHAR column and can’t because a view is built on top of the table.
Suggested action(s)

Temporarily drop the dependent views, which will allow Stitch to widen the columns. This process usually takes about an hour.

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System is in resize mode 

ERROR: Cannot execute query because system is in resize mode
Detail: System is in resize mode, and ONLY read-only queries are allowed to execute.
Applicable to

Amazon Redshift destinations
Level Critical
Category

End-user destination change
Potential cause(s)

Someone adjusted (up or down) the number of nodes of your Amazon Redshift instance and Amazon is currently applying that change.
Suggested action(s)

This is a transient issue. Stitch should be able to resume loading data once the resize is completed.

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Disk is full 

ERROR: Disk Full Detail:
-----------------------------
error:  Disk Full
code:      1016
context:   node: 3
query:     1005177
location:  fdisk_api.cpp:345
process:   query3_66 [pid=27629]
-----------------------------
Applicable to

Amazon Redshift destinations
Level Critical
Category

Destination disk space
Potential cause(s)

The Amazon Redshift instance is full.
Suggested action(s)
  • Add additional nodes to make your Amazon Redshift instance larger, or
  • Remove tables and/or data from the existing instance to free up disk space

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Insufficient table privileges 

ERROR: must be owner of relation [TABLE_NAME]
Applicable to

Amazon Redshift destinations
Level Critical
Category

Database user privileges
Potential cause(s)

Stitch is not the owner of a table in Amazon Redshift, which is required to perform functions necessary to load data.
Suggested action(s)

Verify that the database user authorizing the connection has all the required privileges as outlined in the Amazon Redshift setup instructions.

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Insufficient schema privileges 

ERROR: permission denied for schema [SCHEMA_NAME]
Applicable to

Amazon Redshift destinations
Level Critical
Category

Database user privileges
Potential cause(s)

Stitch does not have privileges to create tables within a schema in Amazon Redshift.
Suggested action(s)

Verify that the database user authorizing the connection has all the required privileges as outlined in the Amazon Redshift setup instructions.

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Database doesn't exist 

FATAL: database "[DATABASE_NAME]" does not exist
Applicable to

Amazon Redshift destinations
Level Critical
Category

Connection settings
Potential cause(s)

Stitch can’t find the database in Amazon Redshift that has been entered into the Destination Settings page.
Suggested action(s)

Verify that the correct database is entered in the Destination Settings page of Stitch.

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Databricks Delta Lake loading errors

Mismatched Amazon S3 and Stitch account regions 

The authorization header is malformed; the region '[STITCH_ACCOUNT_REGION]' is wrong; expecting '[S3_BUCKET_REGION]'
Applicable to

Databricks Delta Lake destinations
Level Critical
Category

Amazon S3 bucket configuration
Potential cause(s)

The Amazon S3 bucket isn’t in the same AWS region as your Stitch account.
Suggested action(s)

Use an Amazon S3 bucket that’s in the same AWS region as your Stitch account. Currently, all Stitch accounts are in the us-east-1 region. Your S3 bucket must be created in this region to use Databricks Delta Lake as your destination.

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Google BigQuery loading errors

Numeric data out of range 

Numeric out of range for BigQuery on [NUMERIC]
Applicable to

All Google BigQuery destination versions
Level Warning
Category

Destination data type limits
Potential cause(s)

Numeric data exceeds the destination’s allowed range.
Suggested action(s)

Remove offending values in the source, or change them to be within the allowed range for Google BigQuery:

Version Range
v1

-99999999999999999999999999999.999999999 to 99999999999999999999999999999.999999999
v2

-99999999999999999999999999999.999999999 to 99999999999999999999999999999.999999999

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Primary Key change is not permitted 

Primary key change is not permitted
Applicable to

Google BigQuery v2 destinations
Level Critical
Category

Primary Keys
Potential cause(s)

The Primary Keys of incoming data don’t match the Primary Keys of the table in the destination.

This can be caused by:

  1. The Primary Keys being changed in the source, or
  2. The _sdc_primary_keys table is altered or dropped
Suggested action(s)

Reset the table(s) mentioned in the error. This will queue a full re-replication of the table(s), which will ensure Primary Keys are correctly captured and used to de-dupe data when loading.

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Microsoft SQL Server loading errors

Primary Key type change is not permitted 

Incoming Primary Key type does not match Primary Key type in existing table
Applicable to

Microsoft SQL Server destinations
Level Critical
Category

Primary Keys
Potential cause(s)

The type of the Primary Key of incoming data doesn’t match the the type of the Primary Key of the table in the destination.

This can be caused by:

  1. The Primary Key type being changed in the source, or
  2. The _sdc_primary_keys table is altered or dropped
Suggested action(s)

Reset the table(s) mentioned in the error. This will queue a full re-replication of the table(s), which will ensure Primary Keys are correctly captured and used to de-dupe data when loading.

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Primary Key change is not permitted 

Incoming Primary Keys do not match Primary Keys in existing table
Applicable to

Microsoft SQL Server destinations
Level Critical
Category

Primary Keys
Potential cause(s)

The Primary Keys of incoming data don’t match the Primary Keys of the table in the destination.

This can be caused by:

  1. The Primary Keys being changed in the source, or
  2. The _sdc_primary_keys table is altered or dropped
Suggested action(s)

Reset the table(s) mentioned in the error. This will queue a full re-replication of the table(s), which will ensure Primary Keys are correctly captured and used to de-dupe data when loading.

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PostgreSQL loading errors

Insufficient schema privileges 

Encountered error while attempting to create new schema.
Applicable to

All PostgreSQL-backed destinations
Level Critical
Category

Database user privileges
Potential cause(s)

Stitch is unable to create or load data into a schema in your destination. This is usually due to insufficient database user privileges.
Suggested action(s)

Verify that the Stitch database user has the required permissions, as outlined here.

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Disk is full 

ERROR: could not extend file "base/16389/t2_285302": No space left on device
Hint: Check free disk space.
Where: COPY staging_0_[FILE_NAME], line [LINE_NUMBER]
Applicable to

All PostgreSQL-backed destinations
Level Critical
Category

Destination disk space
Potential cause(s)

The PostgreSQL instance is full.
Suggested action(s)
  • Add additional space to make your PostgreSQL database larger, or
  • Remove tables and/or data from the existing instance to free up disk space

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Insufficient storage space 

ERROR: could not write block XXXX of temporary file: No space left on device
Applicable to

All PostgreSQL-backed destinations
Level Critical
Category

Destination disk space
Potential cause(s)

The PostgreSQL instance is full.
Suggested action(s)
  • Add additional space to make your PostgreSQL database larger, or
  • Remove tables and/or data from the existing instance to free up disk space

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Snowflake loading errors

Primary Key change is not permitted 

Keys for table do not match Primary Keys of incoming data
Applicable to

Snowflake destinations
Level Critical
Category

Primary Keys
Potential cause(s)

The Primary Keys of incoming data don’t match the Primary Keys of the table in the destination.

This can be caused by:

  1. The Primary Keys being changed in the source, or
  2. The _sdc_primary_keys table is altered or dropped
Suggested action(s)

Reset the table(s) mentioned in the error. This will queue a full re-replication of the table(s), which will ensure Primary Keys are correctly captured and used to de-dupe data when loading.

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