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Posted to dev@sqoop.apache.org by "Attila Szabo (JIRA)" <ji...@apache.org> on 2016/07/06 05:18:10 UTC

[jira] [Commented] (SQOOP-2981) sqoop import from jdbc: JdbcWritableBridge.readBigDecimal() takes a ton of cpu

    [ https://issues.apache.org/jira/browse/SQOOP-2981?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15363788#comment-15363788 ] 

Attila Szabo commented on SQOOP-2981:
-------------------------------------

Hi [~Tagar],

Could you please also perform a profiling with the help of Joremi's tool ( https://github.com/cerndb/Hadoop-Profiler ). It would require JDK8_u60 or above. Is it a doable scenario on your side?

The reason why I'm asking for that is the following:
JdbcWritableBridge#readBigDecimal is just a shorthand for java.sql.ResultSet#getBigDecimal(int), so the implementation is within the Oracle JDBC driver, and thus Sqoop do not have too much control over that method.

Meanwhile I'll try to investigate your scenario on my side, and check if I find any clue what could cause you performance issue (or if we could find a workaround e.g. mapping to a different type instead of BigDecimal or so).

Cheers,
Maugli

> sqoop import from jdbc: JdbcWritableBridge.readBigDecimal() takes a ton of cpu
> ------------------------------------------------------------------------------
>
>                 Key: SQOOP-2981
>                 URL: https://issues.apache.org/jira/browse/SQOOP-2981
>             Project: Sqoop
>          Issue Type: Bug
>          Components: codegen, connectors/oracle, sqoop2-jdbc-connector
>    Affects Versions: 1.4.5, 1.4.6
>         Environment: sqoop import from Oracle; saves as parquet file
>            Reporter: Ruslan Dautkhanov
>              Labels: decimal, import, jdbc, oracle, parquet
>
> Majority of time spent of sqoop import from Oracle was on converting Decimal. It was 2.5x times more than following most cpu consumer (snappy compression). 
> Sqoop was 100% on cpu in total, Oracle side was pretty bored.
> {quote}
>  JvmTop 0.8.0 alpha - 11:56:45,  amd64, 48 cpus, Linux 2.6.32-57, load avg 0.92
>  http://code.google.com/p/jvmtop
>  Profiling PID 25489: org.apache.hadoop.mapred.YarnChild 10.20
>   38.78% (     7.68s) com.cloudera.sqoop.lib.JdbcWritableBridge.readBigDecimal()
>   14.27% (     2.82s) org.xerial.snappy.SnappyNative.rawCompress()
>   12.67% (     2.51s) parquet.io.api.Binary$FromStringBinary.encodeUTF8()
>   10.28% (     2.04s) ...quet.column.values.dictionary.DictionaryValuesWriter$()
>    4.80% (     0.95s) ...quet.column.values.fallback.FallbackValuesWriter.writ()
>    3.69% (     0.73s) com.cloudera.sqoop.lib.JdbcWritableBridge.readString()
>    2.51% (     0.50s) parquet.avro.AvroWriteSupport.writeRecordFields()
>    2.30% (     0.46s) parquet.column.impl.ColumnWriterV1.write()
>    1.90% (     0.38s) ...quet.it.unimi.dsi.fastutil.objects.Object2IntLinkedOp()
>    1.31% (     0.26s) ...quet.column.values.rle.RunLengthBitPackingHybridEncod()
>    1.27% (     0.25s) ...quet.column.values.dictionary.DictionaryValuesWriter$()
>    1.22% (     0.24s) parquet.hadoop.CodecFactory$BytesCompressor.compress()
>    0.65% (     0.13s) ...quet.column.values.dictionary.DictionaryValuesWriter$()
>    0.64% (     0.13s) ...quet.it.unimi.dsi.fastutil.objects.Object2IntLinkedOp()
>    0.64% (     0.13s) parquet.bytes.CapacityByteArrayOutputStream.addSlab()
>    0.63% (     0.12s) parquet.io.api.Binary$ByteArrayBackedBinary.getBytes()
>    0.62% (     0.12s) ...quet.column.values.dictionary.DictionaryValuesWriter.()
>    0.58% (     0.12s) parquet.bytes.CapacityByteArrayOutputStream.setByte()
>    0.49% (     0.10s) parquet.hadoop.codec.SnappyUtil.validateBuffer()
>    0.44% (     0.09s) parquet.hadoop.InternalParquetRecordWriter.write()
> {quote}
> DDL of the table on Oracle side:
> {quote}
> CREATE TABLE someschema.sometable
> (
>   ID             NUMBER                         NOT NULL,
>   psn  VARCHAR2(50 BYTE),
>   MERCHID     NUMBER,
>   RECENCY        NUMBER,
>   FREQUENCY      NUMBER,
>   SPEND          NUMBER,
>   SPENDING       NUMBER,
>   FREQ           NUMBER
> )
> {quote}
> Sqoop parameters:
> {quote}
> sqoop import 
>         -Dmapred.job.name="sqoop import into out_table" 
>         --connect "jdbc:oracle:thin:@jdbc_tns" 
>         --username username --password password
>         --direct 
>         --compress --compression-codec snappy 
>         --as-parquetfile 
>         --target-dir hdfs_dir
>         --num-mappers num_mappers
>         --query "SELECT * FROM someschema.sometable WHERE \$CONDITIONS"
> {quote}



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