Category: Polybase

I have a post on Polybase queries against Hadoop which do not generate MapReduce jobs:

The dm_exec_external_work DMV tells us which execution we care about; in this case, I ended up running the same query twice, but I decided to look at the first run of it.  Then, I can get step information from dm_exec_distributed_request_steps.  This shows that we created a table in tempdb called TEMP_ID_14 and streamed results into it.  The engine also created some statistics (though I’m not quite sure where it got the 24 rows from), and then we perform a round-robin query.  Each Polybase compute node queries its temp table and streams the data back to the head node.  Even though our current setup only has one compute node, the operation is the same as if we had a dozen Polybase compute nodes.

Click through for Wireshark-related fun.

James Serra knows how to get my interest:

Polybase was first made available in Analytics Platform System in March 2013, and then in SQL Server 2016.  The announcement at the PASS Summit was that by preview early next year, in addition to Hadoop and Azure blob storage, PolyBase will support Teradata, Oracle, SQL Server, and MongoDB in SQL Server 2016.  And the Azure Data Lake Store will be supported in Azure SQL Data Warehouse PolyBase.

With SQL Server 2016, you can create a cluster of SQL Server instances to process large data sets from external data sources in a scale-out fashion for better query performance (see PolyBase scale-out groups):

I’m excited for the future of Polybase and looking forward to vNext and vNext + 1 (for the stuff which they can’t possibly get done in time for vNext).

I have a post looking at creating external tables in Polybase to hit a Hadoop folder:

The DATA_SOURCE and DATA_FORMAT options are easy:  pick you external data source and external file format of choice.

The last major section deals with rejection.  We’re going from a semi-structured system to a structured system, and sometimes there are bad rows in our data, as there are no strict checks of structure before inserting records.  The Hadoop mindset is that there are two places in which you can perform data quality checks:  in the original client (pushing data into HDFS) and in any clients reading data from HDFS.  To make things simpler for us, the Polybase engine will outright reject any records which do not adhere to the quality standards you define when you create the table.  For example, let’s say that we have a Age column for each of our players, and that each age is an integer.  If the first row of our file has headers, then the first row will literally read “Age” and conversion to integer will fail.  Polybase rejects this row (removing it from the result set stream) and increments a rejection counter.  What happens next depends upon the reject options.

Creating an external table is pretty easy once you have the foundation prepared.

I look at what the deal is with Polybase and Tar files:

The select statement returned 3104 records, exactly 4 shy of the 3108 I would have expected (777 * 4 = 3108).  In each case, the missing row was the first, meaning when I search for LastName = ‘Turgeon’ (the first player in my data set), I get zero rows.  When I search for another second basemen in the set, I get back four rows, exactly as I would have expected.

What’s really interesting is the result I get back from Wireshark when I run a query without pushdown:  it does actually return the row for Casey Turgeon.

This isn’t an ideal scenario, but it did seem to be consistent in my limited testing.

I look at file formats in Polybase:

Delimited text is exactly as it sounds:  you can use a comma, tab, pipe, tilde, or any other delimiter (including multi-character delimiters).  So let’s go through the options here.  First, FORMAT_TYPE must be DELIMITEDTEXT.  From there, we have a few FORMAT_OPTIONS.  I mentioned FIELD_TERMINATOR, which is how we separate the values in a record.  We can also use STRING_DELIMITER if there are quotes or other markers around our string values.

DATE_FORMAT makes it easier for Polybase to understand how dates are formatted in your file.  The MSDN document gives you hints on how to use specific date formats, but you can’t define a custom format today, or even use multiple date formats.

It feels like there’s a new Hadoop file format every day.

I have a post on setting up MapReduce in Polybase:

The short answer is, I’d get errors like the following when I try to run a MapReduce job:

Log Type: stderr
Log Upload Time: Thu Oct 27 00:16:23 +0000 2016
Log Length: 88
Error: Could not find or load main class org.apache.hadoop.mapreduce.v2.app.MRAppMaster

This was a rather vexing issue for a long time for me.