This is faster than automatic fast-write because it does not copy to the temporary location in S3 first. In addition to the automatic fast-write that happens transparently each time a recipe must write into Redshift, the Sync recipe also has an explicit “S3 to Redshift” engine. The S3 bucket and the Redshift cluster must be in the same Amazon AWS region In order for automatic fast-write to work, the following are needed: Note that when running visual recipes directly in-database, this does not apply, as the data does not move outside of the database. This should not be a path containing datasets.ĭSS will now automatically use the optimal S3-to-Redshift copy mechanism when executing a recipe that needs to load data “from the outside” into Redshift, such as a code recipe. This is a temporary path that will be used in order to put temporary upload files. In “Path in connection”, enter a relative path to the root of the S3 connection, such as “redshift-tmp”. In “Auto fast write connection”, enter the name of the S3 connection to use Then, in the settings of the Redshift connection: The recommended way to load data into Redshift is through a bulk COPY from files stored in Amazon S3.ĭSS can automatically use this fast load method. Loading data into Redshift using the regular SQL “INSERT” or “COPY” statements is extremely inefficient (a few dozens of records per second) and should only be used for extremely small datasets. “Automatic fast-write” write to Redshift (see below for details) is not supported Reading external tables (also known as Redshift Spectrum) is not supported Using an IAM role for connecting is not supportedįor read-write connections, a single output schema must be selected In your launchpad, select “Add Feature”, then “Redshift” (either read-only or read-write) In the connection settings, set “Redshift driver (user-provided)” as “Driver to use”, and enter lib/jdbc/redshift-dedicated as “Driver jars directory”. Reading or writing more than 2 billion records from/to a Redshift dataset (apart from using the In-database SQL engine)Ĭreate a new folder under DATA_DIR/lib/jdbc, such as DATA_DIR/lib/jdbc/redshift-dedicatedĬopy the redshift-jdbc42-X.Y.Z.T.jar file to DATA_DIR/lib/jdbc/redshift-dedicated Reading external tables (also known as “Redshift Spectrum”) The dedicated driver is required for the following capabilities: When setting up the connection, you can choose which driver to use. Redshift can use a dedicated Redshift driver Setting up (Dataiku Custom or Dataiku Cloud Stacks) ¶ Selecting the JDBC driver ¶ Setting up (Dataiku Custom or Dataiku Cloud Stacks)Ĭontrolling distribution and sort clauses The rest of this page is primarily reference information for Redshift.ĭSS supports the full range of features on Redshift: You might want to start with our detailed tutorial for your first steps with SQL databases in DSS. API Node & API Deployer: Real-time APIs.Automation scenarios, metrics, and checks.Controlling distribution and sort clauses.Setting up (Dataiku Custom or Dataiku Cloud Stacks).
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