Google Cloud Storage

Guide to integrate your Google Cloud Storage to Sprinkle

Datasource Concepts

Before setting up the datasource, learn about datasource concepts here

Step by Step Guide

STEP-1: Configure Google Cloud Storage Connection

To learn about Connection, refer here

  • Log into Sprinkle application

  • Navigate to Datasources -> Connections Tab -> New Connection ->

  • Select Google Cloud Storage

  • Provide all the mandatory details

    • Name: Name to identify this connection

    • Bucket Name

    • Private Key JSON: Private credential that is specified in JSON format, to know more, click here.

  • Test Connection

  • Create

STEP-2: Configure Google Cloud Storage datasource

To learn about datasource, refer here

  • Navigate to Datasources -> Datasources Tab -> Add ->

  • Select Google Cloud Storage

  • Provide the name -> Create

  • Connection Tab:

    • From the drop-down, select the name of connection created in STEP-2

    • Update

STEP-3: Create Dataset

Datasets Tab: To learn about Dataset, refer here. Add Dataset for each folder that you want to replicate, providing following details

  • File Type: Select the File Format

    • JSON

    • CSV

      • Select Delimiter - Comma, Tab, Pipe, Dash, Other Character

      • Skip before header - Specify the number of rows to skip before header line. Should not skip column header itself.

      • Exclude columns - specify columns to exclude using comma(,) separated. Ex - column1,column2

    • Parquet

    • ORC

  • Directory Path (Required) :Provide the full path like this: gs://test-sprinkle-bucket/sprinkle//bigquery/datasource/big

  • Ingestion Mode (Required) :

    • Complete: Full folder is downloaded and ingested in every ingestion job run

    • Incremental: Ingest only the new files in every ingestion job run. Use this option if your folder is very large, and you are getting new files continuously

      • Remove Duplicate Rows:

        • Unique Key: Unique key from table, to dedup data across multiple ingestions

        • Time Column Name: Will be used to order data for deduping

      • Max Job Runtime: Give maximum time in minutes for which data should be downloaded. Ingestion job will run specified max minutes and checkpoint will be updated. Next run will continue from checkpoint.

  • Flatten Level (Required): Select One Level or Multi Level. In one level, flattening will not be applied on complex type. They will be stored as string. In multi level, flattening will be applied in complex level till they become simple type.

  • Destination Schema (Required) : Data warehouse schema where the table will be ingested into

  • Destination Table name (Required) : It is the table name to be created on the warehouse. If not given, sprinkle will create like ds_<datasourcename>_<tablename>

  • Destination Create Table Clause: Provide additional clauses to warehouse-create table queries such as clustering, partitioning, and more, useful for optimizing DML statements. Learn more on how to use this field.

  • Create

STEP-4: Run and schedule Ingestion

In the Ingestion Jobs tab:

  • Trigger the Job, using Run button

  • To schedule, enable Auto-Run. Change the frequency if needed

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