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From Buntu Dev <buntu...@gmail.com>
Subject Re: sqoop export -- mysql upsert performance
Date Tue, 24 Jun 2014 18:22:25 GMT
Thanks Gwen for the response.

Tried with 4 mappers, 100 records.per.statement and 100
statements.per.transactions.. got much lower throughput:

[ExportJobBase] - Transferred 788.9209 KB in 623.7671 seconds (1.2648
KB/sec)
[ExportJobBase] - Exported 63787 records.

With 1 mapper it was too slow and we had to kill the job.

When we tried with 100/100/100.. notice for same number of records the
amount of data transferred is 5.9855MB vs 788KB from previous run:

[ExportJobBase] - Transferred 5.9855 MB in 47.9844 seconds (127.7323 KB/sec)
[ExportJobBase] - Exported 63787 records.

Do we need to add the unique key on 'user_id' (already has primary key) as
the INSERT statement constructed by sqoop seems fine.



On Mon, Jun 23, 2014 at 2:54 PM, Gwen Shapira <gshapira@cloudera.com> wrote:

> You are using super high number of mappers for very low amounts of data
> (50MB or less) and getting very low throughput (less than 1MB/s)
>
> Can you try same jobs with just 1 mapper? And 4 mappers?
>
> Gwen
>
>
>
> On Mon, Jun 23, 2014 at 2:32 PM, Buntu Dev <buntudev@gmail.com> wrote:
>
>> Hi,
>>
>> We are using sqoop (v1.4.4) export for exporting the uniques per user_id
>> into the mysql table with 2 integer columns and with 'user_id' as the
>> unique key with these options:
>>
>>  sqoop export \
>>             -Dsqoop.export.records.per.statement=1000 \
>>             -Dsqoop.export.statements.per.transaction=1 \
>>             --connect "jdbc:mysql://host/db" \
>>             --username user \
>>             --password pwd \
>>             --table tbl \
>>             --batch \
>>             --relaxed-isolation \
>>             --update-mode allowinsert \
>>             --update-key user_id \
>>             --export-dir output/dir/ \
>>             --input-fields-terminated-by '\t' \
>>             --input-lines-terminated-by '\n' \
>>             --num-mappers=200
>>
>> Are the options such as batching, records/statement or statements per
>> transaction applicable in case of the MySQL upserts?
>>
>> Also, we are noticing that for smaller jobs the throughput of the export
>> job is higher compared to the larger jobs:
>>
>> large job:
>> [ExportJobBase] - Transferred 37.3672 MB in 838.2908 seconds (45.6452
>> KB/sec)
>> [ExportJobBase] - Exported 3025677 records.
>>
>> small job:
>> [ExportJobBase] - Transferred 12.0951 MB in 40.9846 seconds (302.1965
>> KB/sec)
>> [ExportJobBase] - Exported 88042 records.
>>
>> and bumping up the mappers to 400 has similar behavior as well:
>>
>> large job:
>> [ExportJobBase] - Transferred 49.6578 MB in 638.6147 seconds (79.6249
>> KB/sec)
>> [ExportJobBase] - Exported 3243995 records.
>>
>> small job:
>> [ExportJobBase] - Transferred 24.4653 MB in 59.1785 seconds (423.3366
>> KB/sec)
>> [ExportJobBase] - Exported 139181 records.
>>
>> Attempting to remove batch option or increasing the number of statements
>> per transaction causes lock wait timeout exceeded exceptions.
>>
>> Please let me know if there is anything obvious we might be missing.
>>
>> Thanks!
>>
>
>

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