If you did not see it yet, check out this patch: https://issues.apache.org/jira/browse/SQOOP-1341
It may solve your issue. If user_id is a primary key, you don't need to add a unique key. Primary keys are always unique. Gwen On Tue, Jun 24, 2014 at 11:22 AM, Buntu Dev <[email protected]> wrote: > 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 <[email protected]> > 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 <[email protected]> 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! >>> >> >> >
