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Evaluation of cloudera impala 1.1
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Yukinori Suda
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I evaluated impala 1.1 on our cluster environment.
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Evaluation of cloudera impala 1.1
1.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / 1 1 Evaluation of Cloudera impala 1.1 Aug 7, 2013 CELLANT Corp. R&D Strategy Division Yukinori SUDA @sudabon
2.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / v Sentry support: l Fine-‐‑‒grained authorization l Role-‐‑‒based authorization v Support for views v Performance improvements l Parquet columnar performance l More efficient metadata refresh for larger installations v Additional SQL l SQL-‐‑‒89 joins (in addition to existing SQL-‐‑‒92) l LOAD function l REFRESH command for JDBC/ODBC v Improved Hbase support: l Binary types l Caching configuration v Fixed many bugs Cloudera Impala 1.1 was released !! 2
3.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / v Hive ⇒ Impala l On Impala shell, can read data in “VIEW” that was created via Hive command ? v Impala ⇒ Hive l On Hive shell, can read data in “VIEW” that was created via Impala command ? v Result Two “VIEW”s have compatibility Check compatibility of “VIEW” 3
4.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / Check performance (Hive on Cluster1) 4 0 50 100 150 200 250 No Comp. Gzip Snappy Gzip Snappy TextFileSequenceFileRCFile 222.039 244.67 239.182 228.801 230.327 Avg. Job Latency [sec] This result will be invalid as performance evaluation cause some data may be read remotely. See the slide of “Check performance (Hive on Cluster2)”.
5.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / Check performance (Impala on Cluster1) 5 0 50 100 150 200 250 No Comp. Gzip Snappy Gzip Snappy Snappy Text File Sequence FileRCFile Parquet File 23.518 32.155 28.617 20.774 12.654 13.146 Avg. Job Latency [sec] This result will be invalid as performance evaluation cause some data may be read remotely. See the slide of “Check performance (Impala on Cluster2)”.
6.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / Check performance (Hive on Cluster2) 6 0 50 100 150 200 250 300 No Comp. Gzip Snappy Gzip Snappy TextFileSequenceFileRCFile 272.176 249.531 245.009 230.034 216.802 Avg. Job Latency [sec]
7.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / Check performance (Impala on Cluster2) 7 0 50 100 150 200 250 300 No Comp. Gzip Snappy Gzip Snappy Snappy Text File Sequence FileRCFile Parquet File 32.528 28.73 21.173 24.794 14.308 19.814 Avg. Job Latency [sec]
8.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / v IMPALA-‐‑‒357 l Insert into Parquet exceed mem-‐‑‒limit v Problem l Even if set mem_̲limit setting, when create ParquetFile table with partitions, consumed memory isnʼ’t limited. l At last, Impalad crashes due to memory shortage v Result CREATE command failed due to memory limit Check fixed bug 8
9.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / v Thanks to dev. team, Impala is also going from “Good to Great” v Both “VIEW” and “Parquet” are already ready v Performance v RCFile+Snappy is the fastest on both Cluster1 and Cluster2 v If use larger size table, Parquet+Snappy may be the fastest v Hope for future extension l Support Structure Types l Support UDF/UDTF, etc Summary 9
10.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / 10 Appendix. Benchmark Details
11.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / Our System Environment(Cluster1) 11 v Install using Cloudera Manager Free Edition 4.6.0 Master Slave 14 Servers All servers are connected with 1Gbps Ethernet through an L2 switch Active NameNode DataNode TaskTracker Impalad Stand-‐‑‒by NameNode JobTracker statestored 3 Servers DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode DataNode DataNode DataNode
12.
Copyright © CELLANT
Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / Our System Environment(Cluster2) 12 v Install using Cloudera Manager Free Edition 4.6.0 Master Slave 10 Servers All servers are connected with 1Gbps Ethernet through an L2 switch Active NameNode DataNode TaskTracker Impalad Stand-‐‑‒by NameNode JobTracker statestored 3 Servers DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode TaskTracker Impalad DataNode DataNode DataNode DataNode Decommissioned
13.
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Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / v CPU l Intel Core 2 Duo 2.13 GHz with Hyper Threading v Memory l 8GB : Namenodes only l 4GB : Others v Disk l 7,200 rpm SATA mechanical Hard Disk Drive * 1 v OS l Cent OS 6.3 Our Server Specification 13
14.
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Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / v Use CDH4.3.0 + Impala 1.1 v Use hivebench in open-‐‑‒sourced benchmark tool “HiBench” l https://github.com/hibench v Modified datasets to 1/10 scale l Default configuration generates table with 1 billion rows v Modified query sentence l Deleted “INSERT INTO TABLE …” to evaluate read-‐‑‒only performance v Combines a few storage format with a few compression method l TextFile, SequenceFile, RCFile, ParquestFile l No compression, Gzip, Snappy v Comparison with job query latency v Average job latency over 5 measurements v Benchmark on both Cluster1 and Cluster2 Benchmark 14
15.
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Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / • Uservisits table – 100 million rows – 16,895 MB as TextFile – Table Definitions • sourceIP string • destURL string • visitDate string • adRevenue double • userAgent string • countryCode string • languageCode string • searchWord string • duration int • Rankings table – 12 million rows – 744 MB as TextFile – Table Definitions • pageURL string • pageRank int • avgDuration int Modified Datasets 15
16.
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Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / SELECT sourceIP, sum(adRevenue) as totalRevenue, avg(pageRank) FROM rankings_̲t R JOIN [BROADCAST] ( SELECT sourceIP, destURL, adRevenue FROM uservisits_̲t UV WHERE (datediff(UV.visitDate, '1999-‐‑‒01-‐‑‒01')>=0 AND datediff(UV.visitDate, '2000-‐‑‒01-‐‑‒01')<=0) ) NUV ON (R.pageURL = NUV.destURL) group by sourceIP order by totalRevenue DESC limit 1; Modified Query 16
17.
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Corp. All Rights Reserved. h t t p : / / w w w . c e l l a n t . j p / 17 Thanks! I want to use TPC in next evaluation…
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