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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 source 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:
COPY INTO - Enables loading data from staged files to an existing table.
CREATE TABLE [USING] - Enables loading data from some external sources like JDBC.
CREATE TABLE - Creates table in our case temporary table.
INSERT INTO - Inserts new rows into a table.
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Snap Type
Databricks - Bulk Load Snap is a write-type Snap that loads data into your DLP instance.
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Type | Format | Number of Views | Examples of Upstream and Downstream Snaps | Description |
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Input | Document |
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| This Snap allows two viewscan read from two input documents at a time:
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Output | Document |
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| 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 while running the Pipeline by choosing one of the following options from the When errors occur list under the Views tab. The available options are:
Learn more about Error handling in Pipelines. |
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Field Name | Field Type | Field Dependency | Description | |||
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Label* Default Value: Databricks - Bulk Load | String | None. | 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. | |||
Database name Default Value: None. | String/Expression/Suggestion | None. | 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. | |||
Table Name* Default Value: None. | String/Expression/Suggestion | None. | Enter the name of the table in which you want to perform the bulk load operation. | |||
Source Type Default Value: Cloud Storage File | Dropdown list | None. | Select the type of source from which you want to load the data into your DLP instance. The available options are:
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Load action* Default Value: Drop and create table | Dropdown list | None. | Select the appropriate load action you want to perform on the target table for this bulk upload operation. You can:
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Source table name | String | Source Type is JDBC. | Enter the source table name. The default values (database) configured in the Snap’s account for JDBC Account type are considered, if not specified in this field. | |||
Target Table Columns | Source Type is Cloud Storage file or JDBC and Load action is Drop and create table. | Use this fieldset to specify the target table schema for creating a new table. Specify the Column Name and Data Type for as many columns you need to load in the target table. | ||||
Column Default Value: None. | String | None. | Enter the name of the column that you want to load in the target table. | |||
Data Type Default Value: None. | String | None. | Enter the data type of the values in the specified column. | |||
File format type Default Value: CSV | Dropdown list | Source Type is Cloud Storage file. | Select the file format of the source data file. It can be CSV, JSON, ORC, PARQUET, or TEXT. | |||
File Format Option List | 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 Default Value: None. | String/Expression/Suggestion | 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. | |||
Files provider Default Value: File list | Dropdown list | 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. | |||
File list | Source Type is Cloud Storage file and Files provider is File list. | You can use this field set to specify the file paths to be used for the bulk load operation. Choose one file path in each row. | ||||
File Default Value: None. | String | 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. | |||
File pattern Default Value: None. | String/Expression | 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. | |||
Encryption type Default Value: None. | String | Source Type is Cloud Storage file. | Select the encryption type that you want to use for decrypting the loaded source data and/or files staged in the S3 buckets.
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KMS key Default Value: None. | String/Expression | 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. | |||
Snap Execution Default Value: Execute only | Dropdown list | None. | Select one of the three modes in which the Snap executes. Available options are:
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Bulk Loading of Employee data from a CSV file into a DLP instance
<Work in Progress>Consider the scenario where we need the employee data from a CSV file be fed into a DLP instance so that we can analyze the data.
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We need two Snaps—one to load the data from the CSV file and another to read the data loaded in the target table and generate some insights.
We configure the Databricks - Bulk Load Snap to load employee data from the CSV into a new table, company_employees.
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Here is how we do it:
Select the Drop and create table as the Load action.
Define the schema for the new table in the Target Table Columns fieldset.
Choose the source data type and indicate that the file contains a valid header.
Specify the file names (with relative paths, here) to load the data from.
As our CSV file in the S3 location is not encrypted, we leave the corresponding fields blank.
Upon running the Snap, it loads the entire valid data into the target table and displays the new table name and the number of records loaded.
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Next, to read the data from the new table in the DLP instance, we use the Databricks - Select Snap. We provide the Table name and configure the Snap with a WHERE clause, salary < 500000.
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Upon validation, the Snap retrieves and displays the data from the company_employees table that matches the WHERE condition specified.
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