Redshift - S3 Upsert

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Snap Type:



This Snap executes a Redshift S3 upsert. This Snap directly upserts (inserts or updates) data from a file (source) on a specified Amazon S3 location to the target Redshift table. A temporary table is created on Redshift with the contents of the staging file. An update operation is then run to update existing records in the target table and/or an insert operation is run to insert new records into the target table.

Refer to AWS Amazon documentation for more information.

ETL Transformations & Data Flow

The Redshift S3 Upsert Snap loads the data from the given list of s3 files using the COPY command and inserts the data if not already in the the redshift table using INSERT ALL query or update if it exists.

Input & Output:

InputThis Snap can have an upstream Snap that can pass values required for expression fields.

OutputA document that contains the result providing the number of documents being inserted/ updated/ failed.


  • The Redshift account does need to specify the Endpoint, Database name, Username, and Password.
  • The Redshift account does need to specify the S3 Access-key ID, S3 Secret key, S3 Bucket, and S3 Folder.
  • The Redshift account security settings does need to allow access from the IP Address of the cloudplex or groundplex.

IAM Roles for Amazon EC2

The 'IAM_CREDENTIAL_FOR_S3' feature is used to access S3 files from EC2 Groundplex, without Access-key ID and Secret key in the AWS S3 account in the Snap. The IAM credential stored in the EC2 metadata is used to gain access rights to the S3 buckets. To enable this feature, the following line should be added to and the jcc (node) restarted:
jcc.jvm_options = -DIAM_CREDENTIAL_FOR_S3=TRUE

Please note this feature is supported in the EC2-type Groundplex only.

For more information on IAM Roles, see

Limitations and Known Issues:

None at the moment.


Account & Access

This Snap uses account references created on the Accounts page of SnapLogic Manager to handle access to this endpoint. The S3 BucketS3 Access-key ID, and S3 Secret key properties are required for the Redshift- S3 Upsert Snap. The S3 Folder property may be used for the staging file. If the S3 Folder property is left blank, the staging file will be stored in the bucket. See Redshift Account for information on setting up this type of account.


InputThis Snap has one input view for the data and a second optional input view for the target table schema.
OutputThis Snap has at most one output view.
ErrorThis Snap has at most one document error view and produces zero or more documents in the view. If you open an error view and expect to have all failed records routed to the error view, you must increase the error count value using Maximum error count field. If the number of failed records exceeds the Maximum error count, the pipeline execution will fail with an exception thrown and the failed records will not be routed to the error view.

None at the moment.



Required. The name for the Snap. You can modify this to be more specific, especially if you have more than one of the same Snap in your pipeline.

Schema name

Required. The database schema name. Selecting a schema filters the Table name list to show only those tables within the selected schema.

The values can be passed using the pipeline parameters but not the upstream parameter.

Example: schema123

Default value: [None]

Table name

Required. Table on which to execute the upsert operation. The property can be given in format of either <schema>.<table_name> or <table_name>. It is suggestible and will retrieve available tables under the schema (if given) during suggest values.

The values can be passed using the pipeline parameters but not the upstream parameter.


  • people
  • "public"."people"

Default value: [None]

Key columns

Required. Columns to use to check for existing entries in the target table.

Example: id

Default value: [None] 

S3 file list

Required. List of S3 files to be loaded into the target table as file names or as expressions.


Default value:  [None] 

IAM Role

Select this property if the bulk load/unload needs to be performed using an IAM role. If selected, ensure the properties (AWS account ID, role name and region name) are provided in the account.

Default value: Not selected

Server-side encryption

This defines the S3 encryption type to use when temporarily uploading the documents to S3 before the insert into the Redshift.  

Default value: Not selected

KMS Encryption type

Specifies the type of KMS S3 encryption to be used on the data. The available encryption options are:

  • None - Files do not get encrypted using KMS encryption
  • Server-Side KMS Encryption If selected, the output files on Amazon S3 are encrypted using this encryption with Amazon S3 generated KMS key. 

Default value: None

If both the KMS and Client-side encryption types are selected, the Snap gives precedence to the SSE,  and displays an error prompting the user to select either of the options only.

KMS key

Conditional. This property applies only when the encryption type is set to Server-Side Encryption with KMS. This is the KMS key to use for the S3 encryption. For more information about the KMS key, refer to AWS KMS Overview and Using Server Side Encryption

Default value: [None]

Truncate data

Truncate existing data before performing data load. 

With the Bulk Update Snap, instead of doing truncate and then update, a Bulk Insert would be faster.

Default value: Not selected

Update statistics

Update table statistics after data load by performing an analyze operation on the table.

Default value: Not selected

Accept invalid characters

Accept invalid characters in the input. Invalid UTF-8 characters are replaced with a question mark when loading.

Default value: Selected

Maximum error count

Required. A maximum number of rows which can fail before the bulk load operation is stopped. By default, the load stops on the first error.

Example: 10 (if you want the pipeline execution to continue as far as the number of failed records is less than 10)
Default value: 100

Truncate columns

Truncate column values which are larger than the maximum column length in the table.

Default value: Selected

Load empty strings

If selected, empty string values in the input documents are loaded as empty strings to the string-type fields. Otherwise, empty string values in the input documents are loaded as null. Null values are loaded as null regardless.

Default value: Not selected

Compression format

The format in which the provided S3 files are compressed in. Specifies:

  • Uncompressed
  • GZIP
  • BZIP2
  • LZOP

Example: GZIP

Default value: Uncompressed

File type

The type of input files. Specifies:

  • CSV
  • JSON
  • ARVO
  • Undefined

Example: JSON

Default value: CSV

Ignore header

Required. Treats the specified number of rows as file headers and does not load them. 

Example: 1

Default value: 0


The single ASCII character that is used to separate fields in the input file, such as a pipe character ( | ), a comma (, ), or a tab ( \t ). Non-printing ASCII characters are supported. ASCII characters can also be represented in octal, using the format '\ddd', where 'd' is an octal digit (0–7). The default delimiter is a pipe character ( | ), unless the CSV parameter is used, in which case the default delimiter is a comma (, ). The AS keyword is optional. DELIMITER cannot be used with FIXEDWIDTH.


Default value: pipe character ( | )

Additional options

Additional options to be passed to the COPY command. 

Refer to AWS Amazon - COPY documentation for available options.


Default value:  [None] 

Vacuum type

Reclaims space and sorts rows in a specified table after the upsert operation. The available options to activate are FULL, SORT ONLY, DELETE ONLY and REINDEX. Please refer to the AWS Amazon - VACUUM documentation for more information.


Default value:  [None] 

Vacuum threshold (%)

Specifies the threshold above which VACUUM skips the sort phase. If this property is left empty, Redshift sets it to 95% by default.

Default value:  [None] 

Snap Execution

Select one of the three modes in which the Snap executes. Available options are:

  • Validate & Execute: Performs limited execution of the Snap, and generates a data preview during Pipeline validation. Subsequently, performs full execution of the Snap (unlimited records) during Pipeline runtime.
  • Execute only: Performs full execution of the Snap during Pipeline execution without generating preview data.
  • Disabled: Disables the Snap and all Snaps that are downstream from it.

Redshift's Vacuum Command

In Redshift, when rows are DELETED or UPDATED against a table they are simply logically deleted (flagged for deletion), not physically removed from disk. This causes the rows to continue consuming disk space and those blocks are scanned when a query scans the table. This results in an increase in table storage space and degraded performance due to otherwise avoidable disk IO during scans. A vacuum recovers the space from deleted rows and restores the sort order. 

Groundplex System Clock and Multiple Snap Instances with the same 'S3 file list' property

  1. The system clock of the Goundplex should be accurate down to less than a second. The Snap executes Redshift COPY command to have Redshift load CSV data from S3 files to a temporary table created by the Snap. If Redshift fails to load any record, it stores the error information for each failed CSV record into the system error table in the same Redshift database. Since all errors from all executions go to the same system error table, the Snap executes a SELECT statement to find the errors related to a specific COPY statement execution. It uses WHERE clause including the CSV filenames, start time and end time. If the system clock of Groundplex is not accurate down to less than a second, the Snap might fail to find error records from the error table.
  2. If multiple instances of the Redshift - S3 Upsert Snap have the same S3 file list property value and execute almost same time, the Snap will fail to report correct error documents in the error view. Users should make sure each Redshift - S3 Upsert Snap instance with the same S3 file list executes one at a time.


Basic Use Case

The following pipeline describes how the Snap functions as a standalone Snap in a pipeline:

Step1: Provide a valid Redshift account and database/ table name to upload all the documents in the target table.
Step2: Provide a valid S3 account parameters and S3 file list parameter to copy the list of documents.
Step3: Make sure to choose the proper parameters in the Settings tab and invoke the pipeline.

Below is a preview of the output from the Redshift S3 Upsert Snap depicting that four records have been inserted into the table:


We can also verify the same by checking it in Redshift database:

Refer to the "Redshift - S3 Upsert_2017_10_16.slp" in the Download section for more reference

Typical Snap Configurations

Key configuration of the Snap lies in how S3 file list are passed to perform the upsert of the records. The S3 file lists can be passed:

  • Without Expressions:

The values are passed directly to the snap

  • With Expressions:
    • Using Pipeline parameters:

The table name, Key columns and S3 file list can be passed as the pipeline parameter

The Redshift S3 Upsert Snap with the pipeline parameter as the Table name/ S3 file list/ Key column:

Advanced Use Case

The following pipeline describes how the Snap functions as a standalone Snap in a pipeline by passing some invalid values (Trying to pass invalid UTF-8 characters in the bpchar(1) column created in Redshift table)

Below is the table structure in Redshift: 

We are then trying to pass a CSV files with some invalid characters (with 6 invalid records). CSV file "chartablefors3_new.csv" has been attached in the Downloads section. Also trying to accept the Invalid characters in the Redshift table by specifying the same in "Additional Options" as show below in the snap configuration:

ACCEPTINVCHARS [AS] ['replacement_char'] enables loading of data into VARCHAR columns even if the data contains invalid UTF-8 characters. When ACCEPTINVCHARS is specified, COPY replaces each invalid UTF-8 character with a string of equal length consisting of the character specified by replacement_char. ACCEPTINVCHARS is valid only for VARCHAR columns. Refer to the AWS Amazon documentation - Data Conversion for more information.

Since the data type provided is bpchar which will throw an error for 6 records.

Below is a preview of the output from the Redshift S3 Upsert Snap depicting that three records have been updated into the table and other six records have been failed:

Errors are shown below for your reference:

Refer to the "Redshift S3 Upsert - additional options.slp" in the Download section for more reference


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Related Information

This section gives you a consolidated list of internal and external resources related to this Snap:

Older Examples

  Redshift S3 Upsert with a single S3 CSV file

In this pipeline, the Redshift Execute Snap creates a table on a Redshift Database server. The Redshift S3 Upsert Snap upserts the records into the table from a file on an S3 location.

The Redshift Execute Snap creates the table, snap1222_emp2 on the Redshift Database server.

The success status is as displayed below:

The S3 Upsert Snap upserts the records from the file Emp_S3.csv , from an S3 location on to the table, snap1222_emp2 on the Redshift Database.

Additionally, the IAM role is selected, and hence ensure that the table structure is same as on the file on S3 location.

The successful execution of the pipeline displays the below output preview:

 Upsert data into a file on Amazon S3.

Example # 1

In this example, the table,  customer_interleaved in the schema, prasanna, is read and the s3:///patan/customer_interleaved.csv file is upserted (updated or inserted) with records. The table that is read and the file that is updated exists in Amazon S3. 

The successful execution of the pipeline displays the output preview where 2 records have been updated:

Example # 2

The example assumes that you have configured & authorized a valid Redshift account (see Redshift Account) to be used with this Snap. In the following example, employee_1 table in the schema, space in schema, is read and the employee_1.csv file is upserted (updated or inserted) with records. The table that is read and the file that is updated exists in Amazon S3.

See Also

Redshift IAM Account Setup

  • If the EC2 plex (where your Pipeline is running with IAM role), Redshift cluster, and S3 bucket are in the same AWS account, then you must use Redshift Account (normal IAM account).
  • If the EC2 plex (where your Pipeline is running with IAM role) is in one account and the Redshift cluster and S3 bucket are in a different AWS account, you must use Redshift Cross-account IAM role Account to run your Pipelines successfully.

This is applicable only for Redshift - Bulk Load, Redshift - Unload, and Redshift - S3 Upsert Snaps.