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From Joshua Baxter <joshuagbax...@gmail.com>
Subject Re: Using more than a single mapper per partition with OraOop
Date Thu, 06 Nov 2014 19:24:01 GMT
Hi David,

Thanks for your reply. I think the incorrect chunking is exactly my
problem. I've now changed that, however i have hit a couple more issues.
Firstly, after launching the job I am now getting the following error
 after the query to fetch the block information.

14/11/06 14:17:58 ERROR tool.ImportTool: Encountered IOException running
import job: java.io.IOException: java.sql.SQLException: Numeric Overflow
        at
com.quest.oraoop.OraOopDataDrivenDBInputFormat.getSplits(OraOopDataDrivenDBInputFormat.java:120)
        at
org.apache.hadoop.mapreduce.JobSubmitter.writeNewSplits(JobSubmitter.java:498)
        at
org.apache.hadoop.mapreduce.JobSubmitter.writeSplits(JobSubmitter.java:515)
        at
org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:399)
        at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1295)
        at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1292)
        at java.security.AccessController.doPrivileged(Native Method)
        at javax.security.auth.Subject.doAs(Subject.java:415)
        at
org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1614)
        at org.apache.hadoop.mapreduce.Job.submit(Job.java:1292)
        at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1313)
        at
org.apache.sqoop.mapreduce.ImportJobBase.doSubmitJob(ImportJobBase.java:198)
        at
org.apache.sqoop.mapreduce.ImportJobBase.runJob(ImportJobBase.java:171)
        at
org.apache.sqoop.mapreduce.ImportJobBase.runImport(ImportJobBase.java:268)
        at
org.apache.sqoop.manager.SqlManager.importTable(SqlManager.java:665)
        at
com.quest.oraoop.OraOopConnManager.importTable(OraOopConnManager.java:260)
        at org.apache.sqoop.tool.ImportTool.importTable(ImportTool.java:497)
        at org.apache.sqoop.tool.ImportTool.run(ImportTool.java:605)
        at org.apache.sqoop.Sqoop.run(Sqoop.java:143)
        at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
        at org.apache.sqoop.Sqoop.runSqoop(Sqoop.java:179)
        at org.apache.sqoop.Sqoop.runTool(Sqoop.java:218)
        at org.apache.sqoop.Sqoop.runTool(Sqoop.java:227)
        at org.apache.sqoop.Sqoop.main(Sqoop.java:236)
Caused by: java.sql.SQLException: Numeric Overflow
        at
oracle.jdbc.driver.NumberCommonAccessor.throwOverflow(NumberCommonAccessor.java:4170)
        at
oracle.jdbc.driver.NumberCommonAccessor.getInt(NumberCommonAccessor.java:119)
        at
oracle.jdbc.driver.GeneratedStatement.getInt(GeneratedStatement.java:217)
        at
oracle.jdbc.driver.GeneratedScrollableResultSet.getInt(GeneratedScrollableResultSet.java:522)
        at
oracle.jdbc.driver.GeneratedResultSet.getInt(GeneratedResultSet.java:1350)
        at
com.quest.oraoop.OraOopOracleQueries.getOracleDataChunksExtent(OraOopOracleQueries.java:271)
        at
com.quest.oraoop.OraOopDataDrivenDBInputFormat.getSplits(OraOopDataDrivenDBInputFormat.java:74)
        ... 23 more


Secondly, the query to pull out the block data is taking a really really
long time. About 10 minutes. This query is also running with parallel
querying disabled. Is was wondering if there is any way to enable it for
just this step to help reduce latency?

Thanks

Josh

On Wed, Nov 5, 2014 at 2:00 AM, David Robson <David.Robson@software.dell.com
> wrote:

>  For importing a single partition – you should be able to set the chunk
> method to ROWID, then set oraoop.import.partitions to your partition you
> are importing. This will split that one partition by ROWID to as many
> mappers as you like.
>
>
>
> Also – you shouldn’t need any no parallel hints – the direct connector
> disables parallel query when it first connects so that shouldn’t be a
> problem.
>
>
>
> So in your command below can you change oraoop.chunk.method to ROWID (or
> just leave it out – it is the default) and let me know if that works for
> you?
>
>
>
> *From:* Joshua Baxter [mailto:joshuagbaxter@gmail.com]
> *Sent:* Tuesday, 4 November 2014 8:53 AM
> *To:* user@sqoop.apache.org
> *Subject:* Re: Using more than a single mapper per partition with OraOop
>
>
>
> We will mostly be wanting to bring in a single partition at a time, but
> there will also be occasions where would we need to pull down the whole
> table.
>
>
>
> sqoop import  -Doraoop.import.hint="no_parallel"
> -Doraoop.chunk.method=PARTITION -Doraoop.timestamp.string=false
> -Doraoop.import.partitions=partition_name  --connect connect_string
>  --table "WAREHOUSE.BIG_TABLE" --fetch-size  100000 -m 20 --target-dir
> /user/hive/warehouse/database/partition   --as-parquetfile --username user
> --password password
>
>
>
> On Mon, Nov 3, 2014 at 9:40 PM, Gwen Shapira <gshapira@cloudera.com>
> wrote:
>
> Do you need to get just one partition, or is the ultimate goal to use all
> partitions?
>
>
>
> Also, can you share the exact Oraoop command you used?
>
>
>
> On Mon, Nov 3, 2014 at 1:32 PM, Joshua Baxter <joshuagbaxter@gmail.com>
> wrote:
>
> Apologies if this question has been asked before.
>
>
>
> I have a very large table in Oracle with hundreds of partitions and we
> want to be able to import it to parquet in HDFS a partition at a time as
> part of a ETL process. The table has evolved over time and there is not a
> column that doesn't have significant skew meaning that mappers get very
> uneven numbers when using the standard sqoop connector and split-by. Impala
> is the target platform that the data is for so we also want to keep the
> file sizes under the cluster block size to prevent remote streaming when we
> use the data. I've just discovered OraOop and it sounds like this would be
> exactly tool we would need to import the data in an efficient and
> predictable way.
>
>
>
> Unfortunately the problem i'm now having is that if i use the partition
> option to choose just a single partition this always equates to exactly one
> mapper. The sort of speed and output file sizes we are looking at would
> equate to something like 40.
>
>
>
> Are there any options i can set to increase the number of mappers when
> pulling data from a single table partition?
>
>
>
>
>

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