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From "Pavel Benes (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SQOOP-3014) Sqoop with HCatalog import loose precision for large numbers that does not fit into double
Date Fri, 23 Sep 2016 06:22:20 GMT

     [ https://issues.apache.org/jira/browse/SQOOP-3014?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Pavel Benes updated SQOOP-3014:
-------------------------------
    Attachment:     (was: odbc-bdpdev.png)

> Sqoop with HCatalog import loose precision for large numbers that does not fit into double
> ------------------------------------------------------------------------------------------
>
>                 Key: SQOOP-3014
>                 URL: https://issues.apache.org/jira/browse/SQOOP-3014
>             Project: Sqoop
>          Issue Type: Bug
>          Components: hive-integration
>    Affects Versions: 1.4.6
>            Reporter: Pavel Benes
>            Priority: Critical
>
> When using sqoop with HCatalog to import data from JDBC (I have tried Oracle11) all numbers
that does not fit into double are loosing its precision or are distorted.
> Steps to reproduce:
> 1) Create test table in Oracle and fill it with test data
> {code}
> CREATE TABLE TEST_SQOOP_ERROR(ID VARCHAR(10), TYPE_NUMBER DECIMAL(22,5))
>  
> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-1', 454018528782.42006329)
> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-2', 87658675864540185.123456789123456789)

> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-3', 87658675864540185.12345)
> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-4', 87658675864540185.123)
> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-5', 7658675864540185.12345)

> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-6', 7658675864540185.123456789)

> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-7', 658675864540185.12345)
> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-8', 58675864540185.12345)
> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-9', 8675864540185.12345)

> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-10', 675864540185.12345)

> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-11', 75864540185.12345)

> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-12', 35864540185.12345)

> INSERT INTO MMDINGEST.TEST_SQOOP_ERROR(ID, TYPE_NUMBER) VALUES ( 'row-13', 5864540185.12345)

> {code}
> 2) Create table in Hive database
> {code}
> CREATE TABLE pbe_test_sqoop_error(id string, type_number decimal(22,5)) STORED AS ORC;
> {code}
> 3) Import data from Oracle to Hive using sqoop
> {code}
> export HADOOP_CLASSPATH=/opt/mantis/jdbc/oracle-11.2/ojdbc6.jar
> sqoop import -connect jdbc:oracle:thin:@//1.1.1.1:1521/XE --username  XXX --password
 XXX --hcatalog-database  default --hcatalog-table pbe_test_sqoop_error  --driver oracle.jdbc.OracleDriver
 --query 'SELECT id, type_number FROM MMDINGEST.TEST_SQOOP_ERROR WHERE $CONDITIONS' -m 1
> {code}
> 4) Display data from Hive table
> {code}
> hive> select * from pbe_test_sqoop_error;
> OK
> row-1   454018528782.42004
> row-2   87658675864540192
> row-3   87658675864540192
> row-4   87658675864540192
> row-5   7658675864540185
> row-6   7658675864540185
> row-7   658675864540185.125
> row-8   58675864540185.125
> row-9   8675864540185.12305
> row-10  675864540185.12341
> row-11  75864540185.12344
> row-12  35864540185.12345
> row-13  5864540185.12345
> Time taken: 0.455 seconds, Fetched: 13 row(s)
> {code}
> Only the values at line 1, 12, 13 are correct. At the lines 2-4 even the part of the
number before dot is wrong. All looks correctly in Oracle as can be seen on the attached screenshot.
> The problem seems to be in the java class https://www.codatlas.com/github.com/apache/sqoop/branch-1.4.6/src/java/org/apache/sqoop/mapreduce/hcat/SqoopHCatImportHelper.java
starting at line 437.
> {code}
>     } else if (hfsType == HCatFieldSchema.Type.DECIMAL) {
>       BigDecimal bd = new BigDecimal(n.doubleValue(),
>         MathContext.DECIMAL128);
>       return HiveDecimal.create(bd);
>     }
> {code}
> all numbers, even those that are stored in BigDecimal are squeezed through double which
leads to the precision lost The same issue could be at some places when working with large
numbers.
> The following code fixes this issue:
> {code}
> } else if (hfsType == HCatFieldSchema.Type.DECIMAL) {
>       BigDecimal bd = val instanceof BigDecimal ?  (BigDecimal) val : new BigDecimal(n.doubleValue(),
MathContext.DECIMAL128);
>       return HiveDecimal.create(bd);
>     }
> {code} . 



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