accumulo summit 2014: benchmarking accumulo: how fast is fast?

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Benchmarking Accumulo: How Fast is Fast?

Mike Drob

Software Engineer, Cloudera

Me

• Cloudera Engineer

• Accumulo Committer

• Perpetual Tinkerer

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Victor Grigas CC-BY-SA 3.0

Agenda

• Methodology

• Accumulo 1.4 to 1.6

• Accumulo to HBase

• Conclusions

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Reuvenk CC-BY-SA 2.5

Methodology

• Measuring Performance

• Task Latency (time)

• Throughput (bps)

• Workloads

• Read

• Write

• Mixed

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AngMoKio CC-BY-SA 2.5

Methodology

• Yahoo! Cloud Serving Benchmark

• Workloads

• Connectors

• Highly configurable

• # of Rows/Columns

• Size of Value

• # of Threads

• Parallelizable number of clients

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Sfoskett CC BY-SA 3.0

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Accumulo across versions

Accumulo across versions

• Accumulo 1.4.4-cdh4.5.0

• Accumulo 1.6.0-cdh4.6.0-beta-1

• YCSB 0.14+50

• 80 node cluster

• 10 clients

• 5 racks

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Public Domain via USAF

Accumulo across versions

The Data:

• 200 GB

• 2k Columns

• Pre-Split Table 80x

• Vary # of rows

• Vary value size

(we actually did a lot more,

but it was hard to graph)

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Morio CC BY-SA 3.0

Accumulo across versions

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# of Rows

Aggregate Read

Accumulo 1.4

Accumulo 1.6

Accumulo across versions

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Aggregate Mixed

Accumulo 1.4

Accumulo 1.6

Accumulo across versions

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# of Rows

Aggregate Write

Accumulo 1.4

Accumulo 1.6

Accumulo across versions

• Write speed improved!

• Read speed about the same.

• Something weird happens writing 1000 rows.

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Christopher Foster CC BY-SA 3.0

Accumulo across versions

So, what happens at 1000 rows…? Nothing.

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100

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# of Rows

Problem is at 100 rows.

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Accumulo and HBase

Accumulo and HBase

• Accumulo 1.6.0-cdh4.6.0-beta-1

• HBase 0.94.15-cdh4.6.0

• YCSB 0.14+50

• 5 worker nodes

• 5 split points

• 5G Heap, 3G mem map

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Abdullah AlBargan CC BY-ND 2.0

Accumulo and HBase

• Single client (5 threads)

• Workload sizes

• In memory (15G)

• Force disk activity (30G)

• Constant # of rows

• Vary # of columns

• Activity

• 100% Write

• 100% Read

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nahtanoj CC-BY-2.0

Accumulo and HBase

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# of columns

Reading 15GB (500 rows)

Accumulo

Hbase

Accumulo and HBase

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# of columns

Reading 30GB (1000 rows)

Accumulo

Hbase

Accumulo and HBase

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Writing 15GB (500 rows)

Accumulo

Hbase

Accumulo and HBase

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Writing 30GB (1000 rows)

Accumulo

Hbase

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Performance Tweaks

Performance Tweaks – Client Side

• Number of rows/columns

• Batch Writer Threads

• Batch Writer Buffer Size

• Use large buffer for small values

• Use small buffer for large values

• ACCUMULO-2766 possible fix

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Public Domain via USN

Performance Tweaks – Server Side

• Apply table splits liberally

• Increase automatic split threshold

• Some properties to play with:

• table.compaction.minor.logs.threshold

• tserver.compaction.minor.concurrent.max

• tserver.walog.max.size

• If running with dfs.datanode.synconclose also enable dfs.datanode.sync.behind.writes

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Thank You! Please visit our booth!

Mike Drob – madrob@cloudera.com

@mikhaildrob