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Posted to issues@spark.apache.org by "Sameer Agarwal (JIRA)" <ji...@apache.org> on 2018/01/08 20:42:01 UTC
[jira] [Resolved] (SPARK-17626) TPC-DS performance improvements
using star-schema heuristics
[ https://issues.apache.org/jira/browse/SPARK-17626?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sameer Agarwal resolved SPARK-17626.
------------------------------------
Resolution: Done
Assignee: Ioana Delaney
Fix Version/s: 2.2.0
Target Version/s: 2.2.0 (was: 2.3.0)
> TPC-DS performance improvements using star-schema heuristics
> ------------------------------------------------------------
>
> Key: SPARK-17626
> URL: https://issues.apache.org/jira/browse/SPARK-17626
> Project: Spark
> Issue Type: Umbrella
> Components: SQL
> Affects Versions: 2.1.0
> Reporter: Ioana Delaney
> Assignee: Ioana Delaney
> Priority: Critical
> Fix For: 2.2.0
>
> Attachments: StarSchemaJoinReordering.pptx
>
>
> *TPC-DS performance improvements using star-schema heuristics*
> \\
> \\
> TPC-DS consists of multiple snowflake schema, which are multiple star schema with dimensions linking to dimensions. A star schema consists of a fact table referencing a number of dimension tables. Fact table holds the main data about a business. Dimension table, a usually smaller table, describes data reflecting the dimension/attribute of a business.
> \\
> \\
> As part of the benchmark performance investigation, we observed a pattern of sub-optimal execution plans of large fact tables joins. Manual rewrite of some of the queries into selective fact-dimensions joins resulted in significant performance improvement. This prompted us to develop a simple join reordering algorithm based on star schema detection. The performance testing using *1TB TPC-DS workload* shows an overall improvement of *19%*.
> \\
> \\
> *Summary of the results:*
> {code}
> Passed 99
> Failed 0
> Total q time (s) 14,962
> Max time 1,467
> Min time 3
> Mean time 145
> Geomean 44
> {code}
> *Compared to baseline* (Negative = improvement; Positive = Degradation):
> {code}
> End to end improved (%) -19%
> Mean time improved (%) -19%
> Geomean improved (%) -24%
> End to end improved (seconds) -3,603
> Number of queries improved (>10%) 45
> Number of queries degraded (>10%) 6
> Number of queries unchanged 48
> Top 10 queries improved (%) -20%
> {code}
> Cluster: 20-node cluster with each node having:
> * 10 2TB hard disks in a JBOD configuration, 2 Intel(R) Xeon(R) CPU E5-2680 v2 @ 2.80GHz processors, 128 GB RAM, 10Gigabit Ethernet.
> * Total memory for the cluster: 2.5TB
> * Total storage: 400TB
> * Total CPU cores: 480
> Hadoop stack: IBM Open Platform with Apache Hadoop v4.2. Apache Spark 2.0 GA
> Database info:
> * Schema: TPCDS
> * Scale factor: 1TB total space
> * Storage format: Parquet with Snappy compression
> Our investigation and results are included in the attached document.
> There are two parts to this improvement:
> # Join reordering using star schema detection
> # New selectivity hint to specify the selectivity of the predicates over base tables. Selectivity hint is optional and it was not used in the above TPC-DS tests.
> \\
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