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From "Ryan Blue (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (AVRO-1720) Add an avro-tool to count records in an avro file
Date Wed, 16 Dec 2015 19:33:46 GMT

     [ https://issues.apache.org/jira/browse/AVRO-1720?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Ryan Blue updated AVRO-1720:
    Labels: starter  (was: )

> Add an avro-tool to count records in an avro file
> -------------------------------------------------
>                 Key: AVRO-1720
>                 URL: https://issues.apache.org/jira/browse/AVRO-1720
>             Project: Avro
>          Issue Type: New Feature
>          Components: java
>            Reporter: Janosch Woschitz
>            Priority: Minor
>              Labels: starter
>         Attachments: AVRO-1720-with-extended-unittests.patch, AVRO-1720.patch
> If you're dealing with bigger avro files (>100MB) it would be nice to have a way to
quickly count the amount of records contained within that file.
> With the current state of avro-tools the only way to achieve this (to my current knowledge)
is to dump the data to json and count the amount of records. For bigger files this might take
a while due to the serialization overhead and since every record needs to be looked at.
> I added a new tool which is optimized for counting records, it does not serialize the
records and reads only the block count for each block.
> {panel:title=Naive benchmark}
> {noformat}
> # the input file had a size of ~300MB
> $ du -sh sample.avro 
> 323M    sample.avro
> # using the new count tool
> $ time java -jar avro-tools.jar count sample.avro
> 331439
> real    0m4.670s
> user    0m6.167s
> sys 0m0.513s
> # the current way of counting records
> $ time java -jar avro-tools.jar tojson sample.avro | wc
> 331439 54904484 1838231743
> real    0m52.760s
> user    1m42.317s
> sys 0m3.209s
> # the overhead of wc is rather minor
> $ time java -jar avro-tools.jar tojson sample.avro > /dev/null
> real    0m47.834s
> user    0m53.317s
> sys 0m1.194s
> {noformat}
> {panel}
> This tool uses the HDFS API to handle files from any supported filesystem. I added the
unit tests to the already existing TestDataFileTools since it provided convenient utility
functions which I could reuse for my test scenarios.

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