Databricks - Bulk Load

Overview

You can use this Snap to perform a bulk load operation on your DLP instance. The source of your data can be a file from a cloud storage location, an input view from an upstream Snap, or a table that can be accessed through a JDBC connection. The source data can be in a CSV, JSON, PARQUET, TEXT, or an ORC file.

This Snap uses the following Databricks commands internally:


Prerequisites

  • Valid access credentials to a DLP instance with adequate access permissions to perform the action in context.

  • Valid access to the external source data in one of the following: Azure Blob Storage, ADLS Gen2, DBFS, GCP, AWS S3, or another database (JDBC-compatible).

Limitations

  • Snaps in the Databricks Snap Pack do not support array, map, and struct data types in their input and output documents.

Known Issues

  • For the Databricks - Bulk Load Snap, when the Source is an Input view, data is loaded using the "insert into" command, which is slower in performance compared to the "copy into" command. This performance issue only occurs with Input views. For other cloud sources, the "copy into" command functions properly.

  • The Databricks - Bulk Load Snap fails to execute the DROP AND CREATE TABLE and ALTER TABLE operations on Delta tables when using the Databricks SQL persona on the AWS Cloud. The error message Operation not allowed: ALTER TABLE RENAME TO is not allowed for managed Delta tables on S3 is displayed. However, the same actions run successfully when using the Data Science and Engineering persona on the AWS Cloud. This is a limitation on the Databricks endpoint for serverless configurations or SQL endpoint clusters.

    Cause: This issue arises due to a limitation within the Databricks SQL Admin Console, which prevents you from adding the configuration parameter spark.databricks.delta.alterTable.rename.enabledOnAWS trueto the SQL Warehouse Settings. As a result, the Snap encounters restrictions when attempting to perform certain operations on managed Delta tables stored on Amazon S3.

    Workaround: If you want to use DROP AND CREATE TABLE action in the Databricks - Bulk Load Snap, then connect a Databricks - Execute upstream of the Bulk Load Snap to drop the table using this syntax: DROP TABLE IF EXISTS <target table name>By doing so, the Databricks - Bulk Load Snap does not invoke the ALTER TABLE SQL, and hence the pipeline runs successfully. You can also drop the table through the console before invoking the pipeline that contains the Databricks -Bulk Load Snap.

Snap views

View Description Examples of upstream and downstream Snaps
Input This Snap can read from two input documents at a time:

  • One JSON document for the incoming data to be loaded into the target Databricks instance.

  • Another JSON document that contains the table schema (metadata) for creating the target table.
Output A JSON document containing the bulk load request details and the result of the bulk load operation.
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. The available options are:

  • Stop Pipeline Execution Stops the current pipeline execution when an error occurs.
  • 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

Legend:
  • Expression icon (): Allows using pipeline parameters to set field values dynamically (if enabled). SnapLogic Expressions are not supported. If disabled, you can provide a static value.
  • SnapGPT (): Generates SnapLogic Expressions based on natural language using SnapGPT. Learn more.
  • Suggestion icon (): Populates a list of values dynamically based on your Snap configuration. You can select only one attribute at a time using the icon. Type into the field if it supports a comma-separated list of values.
  • Upload : Uploads files. Learn more.
Learn more about the icons in the Snap settings dialog.
Field / Field set Type Description
Label String

Required. Specify a unique name for the Snap. Modify this to be more appropriate, especially if more than one of the same Snaps is in the pipeline.

Default value: Databricks - Bulk Load

Example: Db_BulkLoad_FromS3
Use unity catalog Checkbox Select this checkbox to use the Unity catalog to access data from the catalog.

Default status: Deselected
Catalog name String/Expression/ Suggestion Specify the name of the catalog for using the unity catalog.

Default value: hive_metastore

Example: xyzcatalog
Database name String/Expression/ Suggestion Enter the name of the database in which the target table exists. Leave this blank if you want to use the database name specified in the Database Name field in the account settings.

Default value: None.

Example: cust_db
Table Name String/Expression/ Suggestion Required. Enter the name of the table in which you want to perform the bulk load operation.

Default value: None.

Example: cust_records
Source Type Dropdown list Select the type of source from which you want to load the data into your DLP instance. The available options are:

  • Cloud Storage File. A file from a cloud location like AWS S3, Azure, or GCS. You can configure a series of options for the bulk load operation as described in this document.

  • Input View. A JSON file coming from the preceding Snap’s output. You need to specify only the Load action.

  • JDBC. A table in another database that can be connected to using a JDBC connector. You can specify the Source table name to load the data from or the Target Table Columns to replace the existing target table with a new one.

Default value: Cloud Storage File

Example: Input View
Load action Dropdown list Select the appropriate load action you want to perform on the target table for this bulk upload operation. You can:

  • Drop and create a table. To remove existing table in the specified database and create a new table with the schema defined below in the Snap, from an Input View, or a JDBC-connected database table.

  • Append rows to existing table. To insert new rows of data to an existing target table.

Default value: Drop and create table

Example: Append rows to existing table
Source table name String Appears when Source Type is JDBC.

Enter the source table name. If not specified in this field, the default values (database) configured in Snap’s account for the JDBC Account type are considered.
Target Table Columns Appears when Source Type is Cloud Storage file or JDBC and Load action is Drop and create table.

Use this field set to specify the target table schema for creating a new table. Specify the Column Name and Data Type for as many columns to load in the target table.
Column String Enter the name of the column that you want to load in the target table.
Data Type String Enter the data type of the values in the specified column.
File format type Dropdown list Appears when Source Type is Cloud Storage file.

Select the file format of the source data file. It can be CSV, JSON, ORC, PARQUET, or TEXT.

Default value: CSV

Example: PARQUET
File Format Option List

Appears when Source Type is Cloud Storage file.

You can use this field set to choose the file format options to associate with the bulk load operation, based on your source file format. Choose one file format option in each row.
File format option String/Expression/ Suggestion Appears when Source Type is Cloud Storage file.

Select a file format option from the available options and set appropriate values to suit your bulk load needs, without affecting the syntax displayed in this field.

Default value: None.

Example: cust_ID
Files provider Dropdown list Appears when Source Type is Cloud Storage file.

Declare the manner in which you are specifying the source files list - File list or pattern. Based on your selection in this field, the corresponding fields change: File list fieldset for File list and File pattern field for pattern.

Default value: File list

Example: pattern
File list

Appears when Source Type is Cloud Storage file and Files provider is File list.

This field set allows you to specify the file paths to be used for the bulk load operation. Choose one file path in each row.
File String Appears when Source Type is Cloud Storage file and Files provider is File list.

Enter the path of the file to be used for the bulk upload operation.

Default value: None.

Example: cust_data.csv
File pattern String/Expression Appears when Source Type is Cloud Storage file and Files provider is pattern.

Enter the regex pattern to use to match the file name and/or absolute path. You can specify this as a regular expression pattern string, enclosed in single quotes. Learn more: Examples of COPY INTO (Delta Lake on Databricks) for DLP.

Default value: None.

Example: folder1/file_[a-g].csv
Encryption type String/Expression/ Suggestion Appears when Source Type is Cloud Storage file.
Select the encryption type to use for decrypting the source data and/or files staged in the S3 buckets.
Tip: Server-side encryption is available only for S3 accounts.

Default value: None.

Example: Server-Side KMS Encryption
KMS key String/Expression Appears when Source Type is Cloud Storage file and Encryption type is Server-Side KMS Encryption.

Enter the KMS key to use to encrypt the files. In case that your source files are in S3, see Loading encrypted files from Amazon S3 for more detail.

Default value: None.

Example: MF96D-M9N47-XKV7X-C3GCQ-G5349
Number of Retries Integer Appears when Source Type is Input View.

Specifies the maximum number of retry attempts when the Snap fails to write.

Example: 3

Minimum value: 0

Default value: 0
Retry Interval (seconds) Integer Appears when Source Type is Input View.

Specifies the minimum number of seconds the Snap must wait before each retry attempt.

Example: 3

Minimum value: 1

Default value: 1
Manage Queued Queries Dropdown list Select this property to determine whether the Snap should continue or cancel the execution of the queued Databricks SQL queries when you stop the pipeline.
Note: If you select Cancel queued queries when pipeline is stopped or if it fails, then the read queries under execution are cancelled, whereas the write type of queries under execution are not cancelled. Databricks internally determines which queries are safe to be cancelled and cancels those queries.
Note: Due to an issue with DLP, aborting an ELT pipeline validation (with preview data enabled) causes only those SQL statements that retrieve data using bind parameters to get aborted while all other static statements (that use values instead of bind parameters) persist.

  • For example, select * from a_table where id = 10 will not be aborted while select * from test where id = ? gets aborted.

To avoid this issue, always configure your Snap settings to use bind parameters inside its SQL queries.

Default value: Continue to execute queued queries when pipeline is stopped or if it fails.

Example: Cancel queued queries when pipeline is stopped or if it fails
Snap execution Dropdown list
Choose 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.

Default value: Execute only

Example: Validate & Execute

Troubleshooting

Error Reason Resolution
Missing property value You have not specified a value for the required field where this message appears. Ensure that you specify valid values for all required fields.

Examples