Snowflake - Bulk Upsert

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Overview

You can use the Snowflake - Bulk Upsert Snap to bulk update existing records or insert records to a target Snowflake table.

Depending on the account that you configure with the Snap, you can use the Snowflake Bulk Upsert Snap to upsert data into AWS S3 buckets or Microsoft Azure Storage Blobs or Google Cloud Storage.

The Snap creates temporary files in the JCC when the staging location is internal and the data source is Input view. These temporary files are removed automatically after the pipeline completes execution.

Snap Type

The Snowflake - Bulk Upsert Snap is a Write-type Snap that performs a bulk upsert operation.

Prerequisites

Security Prerequisites: 

You should have the following permission in your Snowflake account to execute this Snap:

  • Usage (DB and Schema): Privilege to use the database, role, and schema.

The following commands enable minimum privileges in the Snowflake Console:

grant usage on database <database_name> to role <role_name>; grant usage on schema <database_name>.<schema_name>;

For more information on Snowflake privileges, refer to Access Control Privileges.

The below are mandatory when using an external staging location:

When using an Amazon S3 bucket for storage:

  • The Snowflake account should contain S3 Access-key ID, S3 Secret key, S3 Bucket and S3 Folder.

  • The Amazon S3 bucket where the Snowflake will write the output files must reside in the same region as your cluster.

When using a Microsoft Azure storage blob:

  • A working Snowflake Azure database account.

Internal SQL Commands

This Snap uses the following commands internally:

  • SELECT FROM TABLE: SELECT as a statement enables you to query the database and retrieve a set of rows. SELECT as a clause enables you to define the set of columns returned by a query.

  • COPY INTO <table>: Enables loading data from staged files to an existing table. 

  • CREATE TEMPORARY TABLE: Enables creating a temporary table in the database.

  • MERGE: Enables inserting, updating, and deleting values in a table based on values in a second table or a subquery.

Requirements for External Storage Location

The following are mandatory when using an external staging location:

When using an Amazon S3 bucket for storage:

  • The Snowflake account should contain S3 Access-key ID, S3 Secret key, S3 Bucket and S3 Folder.

  • The Amazon S3 bucket where the Snowflake will write the output files must reside in the same region as your cluster.

When using a Microsoft Azure storage blob:

  • A working Snowflake Azure database account.

When using a Google Cloud Storage:

  • Provide permissions such as Public access and Access control to the Google Cloud Storage bucket on the Google Cloud Platform.

Support for Ultra Pipelines

Works in Ultra Pipelines. However, we recommend that you not use this Snap in an Ultra Pipeline.

Limitations

The special character tilde (~) is not supported if it exists in the temp directory name for Windows. It is reserved for the user's home directory.

Known Issues

Because of performance issues, all Snowflake Snaps now ignore the Cancel queued queries when pipeline is stopped or if it fails option for Manage Queued Queries, even when selected. Snaps behave as though the default Continue to execute queued queries when the Pipeline is stopped or if it fails option were selected.

Behavior Change

In the 4.31 main18944 release and later, the Snowflake - Bulk Upsert Snap no longer supports values from an upstream input document in the Key columns field when the expression button is enabled.

To avoid breaking your existing Pipelines that use a value from the input schema in the Key columns field, update the Snap settings to use an input value from Pipeline parameters instead.

Snap Views

Type

Format

Number of Views

Examples of Upstream and Downstream Snaps

Description

Type

Format

Number of Views

Examples of Upstream and Downstream Snaps

Description

Input

Document

  • Min: 1

  • Max: 1

  • JSON Generator

  • Binary to Document

Incoming documents are first written to a staging file on Snowflake's internal staging area. A temporary table is created on Snowflake 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.

Output

Document

  • Min: 0

  • Max: 1

  • Mapper

  • Snowflake Execute

If an output view is available, then the output document displays the number of input records and the status of the bulk upload.

 

Error

Error handling is a generic way to handle errors without losing data or failing the Snap execution. You can handle the errors that the Snap might encounter when running the Pipeline by choosing one of the following options from the When errors occur list under the Views tab:

  • Stop Pipeline Execution: Stops the current pipeline execution if the Snap encounters an error.

  • Discard Error Data and Continue: Ignores the error, discards that record, and continues with the remaining records.

  • Route Error Data to Error View: Routes the error data to an error view without stopping the Snap execution.

Learn more about Error handling in Pipelines.

Snap Settings

  • Asterisk (*): Indicates a mandatory field.

  • Suggestion icon (): Indicates a list that is dynamically populated based on the configuration.

  • Expression icon (): Indicates whether the value is an expression (if enabled) or a static value (if disabled). Learn more about Using Expressions in SnapLogic.

  • Add icon (): Indicates that you can add fields in the field set.

  • Remove icon (): Indicates that you can remove fields from the field set.

Field Name

Field Type

Field Dependency

Description

Field Name

Field Type

Field Dependency

Description

Label*

 

Default ValueSnowflake - Bulk Upsert
Example: Load Employee Tables

String

N/A

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

Schema Name

 

Default Value: N/A
Example: schema_demo

 

 

String/Expression/Suggestion

 

N/A

Specify the database schema name. In case it is not defined, then the suggestion for the Table Name retrieves all tables names of all schemas. The property is suggestible and will retrieve available database schemas during suggest values.

 

Table Name*

 

Default Value: N/A
Example: employees_table

String/Expression/Suggestion

 

N/A

Specify the name of the table to execute bulk load operation on.

 

Staging location

 

Default Value: Internal
Example: External

 

Dropdown list/Expression

N/A

Select the type of staging location that is to be used for data loading:

  • External: Location that is not managed by Snowflake. The location should be an AWS S3 Bucket or Microsoft Azure Storage Blob or Google Cloud Storage. These credentials are mandatory while validating the Account.

  • Internal: Location that is managed by Snowflake.

Flush chunk size (in bytes)

String/Expression

Appears when you select Input view for Data source and Internal for Staging location.

When using internal staging, data from the input view is written to a temporary chunk file on the local disk. When the size of a chunk file exceeds the specified value, the current chunk file is copied to the Snowflake stage and then deleted. A new chunk file simultaneously starts to store the subsequent chunk of input data. The default size is 100,000,000 bytes (100 MB), which is used if this value is left blank.

File format object

 

Default ValueNone

Example: jsonPath()

 

String/Expression

N/A

Specify an existing file format object to use for loading data into the table. The specified file format object determines the format type such as CSV, JSON, XML, AVRO, or other format options for data files.

File format type

 

Default Value: None
Example: CSV

 

String/Expression/Suggestion

N/A

Specify a predefined file format object to use for loading data into the table. The available file formats include CSV, JSON, XML, and AVRO.

File format option

 

Default value:  N/A
Example: BINARY_FORMAT=UTF8

 

String/Expression

 

N/A

Specify the file format option. Separate multiple options by using blank spaces and commas.

Encryption type

 

Default Value: None
Example: Server-Side Encryption

Dropdown list

 

N/A

Specify the type of encryption to be used on the data. The available encryption options are:

  • None: Files do not get encrypted.

  • Server Side Encryption: The output files on Amazon S3 are encrypted with server-side encryption.

  • Server-Side KMS Encryption: The output files on Amazon S3 are encrypted with an Amazon S3-generated KMS key. 

KMS key

 

Default Value: N/A
Example: <Encrypted>

String/Expression

 

 

N/A

Specify the KMS key that you want to use for S3 encryption. Learn more about the KMS key: AWS KMS Overview and Using Server Side Encryption.

Buffer size (MB)

 

Default Value: 10MB
Example: 20MB

String/Expression

 

 

 

N/A

Specify the data in MB to be loaded into the S3 bucket at a time. This property is required when bulk loading to Snowflake using AWS S3 as the external staging area.

Minimum value: 6 MB

Maximum value: 5000 MB

Key columns*

 

Default Value: None 
Example: EmpID

Specify the column to use for existing entries in the target table.

Delete Upsert Condition

 

Default: N/A

 

String

 

N/A

Delete Upsert Condition when true, causes the case to be executed.

Preserve case sensitivity

 

Default Value: Deselected

Checkbox

 

N/A

Select this check box to preserve the case sensitivity of the column names.

  • If you do not select Preserve case sensitivity, the input documents are loaded to the target table if the key names in the input documents match the target table column names ignoring the case.

  • If you include a second input view, selecting Preserve case sensitivity has no effect on the column names of the target table, because Snap uses the metadata from the second input view.

Manage Queued Queries

 

Default Value: Continue to execute queued queries when the Pipeline is stopped or if it fails
Example: Cancel queued queries when the Pipeline is stopped or if it fails

Dropdown list

N/A

Select this property to determine whether the Snap should continue or cancel the execution of the queued Snowflake Execute SQL queries when you stop the pipeline.

Load empty strings

 

Default value:  Selected

Checkbox

N/A

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.

Additional Options

On Error

 

Default Value: ABORT_STATEMENT
Example: CONTINUE

 

 

Dropdown list

N/A

Select an action to perform when errors are encountered in a file. The available actions are:

  • ABORT_STATEMENT: Aborts the COPY statement if any error is encountered. The error will be thrown from the Snap or routed to the error view.

  • CONTINUE: Continues loading the file. The error will be shown as a part of the output document.

  • SKIP_FILE: Skips file if any errors encountered in the file.

  • SKIP_FILE_*error_limit*: Skips file when the number of errors in the file exceeds the number specified in Error Limit.

  • SKIP_FILE_*error_percent_limit*%: Skips file when the percentage of errors in the file exceeds the percentage specified in Error percentage limit.

Error Limit

 

Default Value: 0
Example: 3

 

Integer

Appears when you select SKIP_FILE_*error_limit* for On Error.

Specify the error limit to skip file. When the number of errors in the file exceeds the specified error limit or when SKIP_FILE_number is selected for On Error.

Error Percentage Limit

 

Default Value: 0
Example: 1

Integer

Appears when you select SKIP_FILE_*error_percent_limit*% 
for On Error.

Specify the percentage of errors  to skip file. If the file exceeds the specified percentage when SKIP_FILE_number% is selected for On Error

Snap Execution

 

Default Value: Execute only
Example: Validate & Execute

Dropdown list

N/A

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.

Troubleshooting

Error

Reason

Resolution

Error

Reason

Resolution

Cannot lookup a property on a null value.

The value referenced in the Key Column field is null.

This Snap does not support values from an upstream input document in the Key columns field when the expression button is enabled.

Update the Snap settings to use an input value from pipeline parameters and run the pipeline again.

Data can only be read from Google Cloud Storage (GCS) with the supplied account credentials (not written to it).

Snowflake Google Storage Database accounts do not support external staging when the Data source is the Input view.

Data can only be read from GCS with the supplied account credentials (not written to it).

Use internal staging if the data source is the input view or change the data source to staged files for Google Storage external staging.

Example

Upserting Records

This example Pipeline demonstrates how you can efficiently update and delete data (rows) using the Key Column ID field and Upsert Delete condition. We use Snowflake - Bulk Upsert Snap to accomplish this task.

First, we configure the Mapper Snap with the required details to pass them as inputs to the downstream Snap.

After validation, the Mapper Snap prepares the output as shown below to pass to the Snowflake Bulk - Upsert Snap.

Next, we configure the Snowflake - Bulk Upsert Snap to:

  • Upsert the existing row for P_ID column, (so, we provide P_ID in the Key column field).

  • Delete the rows where the FIRSTNAME is snaplogic in the target table, (so, we specify FIRSTNAME = 'snaplogic' in the Delete Upsert Condition field).

After execution, this Snap inserts a new record into the existing row for the P_ID key column in Snowflake.

Inserted Records Output in JSON

Inserted Records in Snowflake

Inserted Records Output in JSON

Inserted Records in Snowflake

Upon execution, if the Delete Upsert condition is true, the Snap deletes the records in the target table as shown below.

Output in JSON

Deleted Record in Snowflake

Output in JSON

Deleted Record in Snowflake

Download this Pipeline.

Bulk Loading Records

In the following example, we update a record using the Snowflake Bulk Upsert Snap. The invalid records which cannot be inserted will be routed to an error view. 

 

In the pipeline execution:

  1. The Mapper (Data) Snap maps the record details to the input fields of Snowflake Upsert Snap:

     

  2. Snowflake Upsert Snap updates the record using the "PRASANNA"."Persons" table object:

     

  3. Successful execution of the pipeline displays the following data preview (Note that one input has been made and two records with the name P_ID have been updated within the Persons table.):

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