![]() ![]() ![]() How to create a SQL Server Linked Server to Amazon Redshift To the Amazon Redshift database, you will see the following message: Connection Use the port that the cluster was configured to use when it was launched. By default, Amazon Redshift uses port 5439, but you should In the Amazon Redshift console on the cluster’s details page. ![]() As with all target platforms, be aware of any limitations.Specify the endpoint for your Amazon Redshift cluster. In-Database Proceduresįinally, SAS can push the FREQ, RANK, REPORT, SORT, MEANS, and TABULATE procedures into Redshift for execution as SQL queries. In addition to writing your own SQL, SAS DI Studio can generate explicit SQL giving SAS a user interface for Explicit SQL to Redshift. This allows for non-standard SQL commands and complete control of the requests being passed. Explicit Pass-ThroughĪs with most relational databases, SAS can not only pass PROC SQL code implicitly to Redshift, SAS can also send explicit Redshift commands. Implicit Pass-ThroughĪs of SAS 9.4m4, SAS can pass 46 SQL functions as well as most joins to Redshift. SAS can pass instructions in three different ways - Implicit SQL Pass-through Explicit SQL Pass-Through And, In-Database Execution of SAS procedures. ![]() The following table compares the use-case results presented by Jeff and Chris using different load techniques:Įqually as important as load performance, the capability to pass instructions from SAS to Redshift eliminates data transfers all together since data required for SAS queries/processing can stay in Redshift where it is processed. Libname libred redshift server=rsserver db=rsdb user=myuserID pwd=myPwd port=5439 īulkload=yes bl_bucket=myBucket bl_key=99999īl_secret=12345 bl_default_dir='/tmp' bl_region='us-east-1') ĭespite the extra I/O, utilizing the S3 Copy Bulkload mechanism gives SAS impressive performance over even the already-impressive performance of native SAS/Access to Redshift. bulkload=yes) as shown in the following example: They simply have to specify the required bulkload options (e.g. Users don't have to know anything about the COPY command or S3. As of the m4 release, this is all done behind the scenes. Since Redshift will always exist in an AWS Cloud and your SAS server might not, it is critical that SAS can pass data to Redshift as efficiently as possible and that SAS can pass instructions to Redshift so that data is not needlessly passing from Redshift to SAS for processing.Īs Jeff and Chris' paper details, SAS' bulkload mechanism works by pushing the output data to AWS S3 and then issuing an S3 COPY command. Two features standout when discussing Redshift - Bulk-loading and Pass-through/Push-down. Want to see it in action? Check out Chris Dehart's SAS Tech Talk video: The paper's highlights include load method comparisons as well as an excellent description of SAS to Redshift Bulkload mechanism. The paper is behind a release but actually talks about the more recent features in its futures section. In-Database Execution of FREQ, MEANS, RANK, REPORT, SORT, and TABULATEįor a great discussion of all of these features, check out this excellent paper by Chris Dehart and GEL expat, Jeff Bailey.For more details on Redshift, check out this FAQ.Īs of SAS 9.4m4, SAS offers the following Redshift integration: Like Teradata, Redshift distributes its data and processing over multiple hosts allowing it to scale for large implementations. Redshift is an MPP database designed to support reporting, analytics, dashboards, and decisioning. So their database, Redshift, is naturally popular. AWS is arguably the biggest player in the Cloud space. I can tell by counting the requests for information on Amazon Web Services' Redshift. The Cloud Computing universe is also expanding. You can tell by studying the cosmological redshift. ![]()
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