by vaibhav nachankar arvind dwarakanath evaluation of hbase read/write (a study of hbase and it’s...
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BY VAIBHAV NACHANKAR
ARVIND DWARAKANATH
Evaluation of Hbase Read/Write(A study of Hbase and it’s benchmarks)
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Recap of Hbase
Hbase is an open-source, distributed, column-oriented and sorted-map data storage.
It is a Hadoop Database; sits on HDFS.
Hbase can support reliable storage and efficient access of a huge amount of structured data
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Hbase Architecture
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Recap of Hbase (contd.)
Modeled after BigTable.Map/reduce with Hadoop. Optimizations for real time queries.No single point of failure.Random access performance is like MySQL.Application : Facebook Messaging Database.
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Hbase Benchmark Techniques
‘Hadoop Hbase-0.20.2 Performance Evaluation’ by D. Carstoiu, A. Cernian, A. Olteanu. University of Bucharest.
STRATEGY: Uses random read, writes to test and benchmark Hadoop with Hbase.
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Hbase Benchmark Techniques (contd.)
‘Hadoop Hbase-0.20.2 Performance Evaluation’ by Kareem Dana at Duke University. It shows a varied set of test cases for executions to test HBase.
STRATEGY: Tested on column families, columns, Sort and interspersed read/writes.
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Yahoo! Cloud Serving Benchmark (YCSB)
‘Benchmarking Cloud Serving Systems with YCSB’ by Brian F. Cooper, Adam Silberstein, Erwin Tam, Raghu Ramakrishnan, Russell Sears.
This paper/project is designed to benchmark existing and newer cloud storage technologies.
The benchmark is done so far on Hbase, Cassandra, MongoDb, Project Voldemort and SQL.
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YCSB
The benchmark tool uses Workload files and the workload files can be customized according to users.
You can specify 50/50 read/write, 95/5 r/w and so on.
The code for the project is available on Github.
https://github.com/brianfrankcooper/YCSB.git
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Example of a Workload
# Yahoo! Cloud System Benchmark# Workload A: Update heavy workload# Application example: Session store recording recent actions# # Read/update ratio: 50/50# Default data size: 1 KB records (10 fields, 100 bytes each, plus key)# Request distribution: zipfianrecordcount=1000operationcount=1000workload=com.yahoo.ycsb.workloads.CoreWorkloadreadallfields=true
readproportion=0.5updateproportion=0.5scanproportion=0insertproportion=0
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Example of a Workload
# Yahoo! Cloud System Benchmark# Workload B: Read mostly workload# Application example: photo tagging; add a tag is an update, but most operations
are to read tags# # Read/update ratio: 95/5# Default data size: 1 KB records (10 fields, 100 bytes each, plus key)# Request distribution: zipfianrecordcount=1000operationcount=1000workload=com.yahoo.ycsb.workloads.CoreWorkloadreadallfields=true
readproportion=0.95updateproportion=0.05scanproportion=0insertproportion=0
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Our Project
Install Hbase and get Hadoop to interface with it. Study benchmark techniques.
Build a suite of codes and get it to run on Hadoop/Hbase.
Include basic get, put, scan operations.
Extend Word Count’s map-reduce to add to Hbase.
Compare with Brisk Cassandra.
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About Brisk
Cassandra is a No-SQL BigTable-based database.
Datastax enterprise built Brisk to interface Hadoop with Cassandra
Hadoop + Cassandra = Brisk!!
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Brisk Architecture
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Challenges Faced
Configuration of Hbase is a tedious job! Not for the weak of will!
Hbase subsequent releases do not keep the APIs consistent. So we ran into a lot of ‘deprecated API’ error messages.
Hadoop compatibility with Hbase has to be verified before we proceed with installations.
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Challenges Faced (contd.)
Very few documents on installation details of Hbase.
Even fewer for Brisk!
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Performance for Word Count (2 nodes/2 cores each)
1 2 3 4 541
42
43
44
45
46
47
48
49
1 mapper/ 3 reducer
1 mapper/ 3 reducer
Number of readings
Time in secs
Average = 45.484
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Performance for Word Count (contd.)
1 2 3 4 547.5
48
48.5
49
49.5
50
50.5
51
51.5
52
52.5
2 mapper/ 3 reducers
2 mapper/ 3 reducers
Time in secs
Number of readings
Average = 49.664
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Performance for Word Count (contd.)
1 2 3 4 50
10
20
30
40
50
60
2 mapper/ 2 reducers
2 mapper/ 2 reducers
Time in secs
Number of readings
Average = 43.7008
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Performance for a simple get/put/scan (2 nodes/ 2 core)
1 2 3 4 50
0.5
1
1.5
2
2.5
getscanput
Tim
e in
sec
s
Number of readings
Average for get, scan and put are 1.841.6266 and 1.71.
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Performance for Word Count (3 nodes/2 cores each)
1 2 3 4 529
30
31
32
33
34
35
36
37
1 mapper/ 3 reducers
1 mapper/ 3 reducers
Time in secs
Average = 34.047
Number of Readings
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Performance for Word Count (contd.)
1 2 3 4 533
34
35
36
37
38
39
2 mappers/ 3 reducers
2 mappers/ 3 reducers
Number of Readings
Average = 36.1012
Time in secs
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Performance for Word Count (contd.)
1 2 3 4 50
5
10
15
20
25
30
35
40
45
50
2 mappers/ 2 reducers
2 mappers/ 2 reducers
Time in secs
Number of readings
Average = 37.4358
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Conclusions
Brisk seems a lot more promising tool; as it integrates Cassandra and Hadoop together without much ado.
Hbase/Hadoop APIs have to be made consistent. With standardization, it would be easier to work with them.
Hbase Reads are faster than the Writes.
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Thank YouQuestions??