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https://issues.apache.org/jira/browse/SPARK-10392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Davies Liu resolved SPARK-10392.
--------------------------------
Resolution: Fixed
Fix Version/s: 1.6.0
Issue resolved by pull request 8556
[https://github.com/apache/spark/pull/8556]
> Pyspark - Wrong DateType support on JDBC connection
> ---------------------------------------------------
>
> Key: SPARK-10392
> URL: https://issues.apache.org/jira/browse/SPARK-10392
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.4.1
> Reporter: Maciej Bryński
> Fix For: 1.6.0
>
>
> I have following problem.
> I created table.
> {code}
> CREATE TABLE `spark_test` (
> `id` INT(11) NULL,
> `date` DATE NULL
> )
> COLLATE='utf8_general_ci'
> ENGINE=InnoDB
> ;
> INSERT INTO `spark_test` (`id`, `date`) VALUES (1, '1970-01-01');
> {code}
> Then I'm trying to read data - date '1970-01-01' is converted to int. This
> makes data frame incompatible with its own schema.
> {code}
> df =
> sqlCtx.read.jdbc("jdbc:mysql://host/sandbox?user=user&password=password",
> 'spark_test')
> print(df.collect())
> df = sqlCtx.createDataFrame(df.rdd, df.schema)
> [Row(id=1, date=0)]
> ---------------------------------------------------------------------------
> TypeError Traceback (most recent call last)
> <ipython-input-36-ebc1d94e0d8c> in <module>()
> 1 df =
> sqlCtx.read.jdbc("jdbc:mysql://a2.adpilot.co/sandbox?user=mbrynski&password=CebO3ax4",
> 'spark_test')
> 2 print(df.collect())
> ----> 3 df = sqlCtx.createDataFrame(df.rdd, df.schema)
> /mnt/spark/spark/python/pyspark/sql/context.py in createDataFrame(self, data,
> schema, samplingRatio)
> 402
> 403 if isinstance(data, RDD):
> --> 404 rdd, schema = self._createFromRDD(data, schema,
> samplingRatio)
> 405 else:
> 406 rdd, schema = self._createFromLocal(data, schema)
> /mnt/spark/spark/python/pyspark/sql/context.py in _createFromRDD(self, rdd,
> schema, samplingRatio)
> 296 rows = rdd.take(10)
> 297 for row in rows:
> --> 298 _verify_type(row, schema)
> 299
> 300 else:
> /mnt/spark/spark/python/pyspark/sql/types.py in _verify_type(obj, dataType)
> 1152 "length of fields (%d)" % (len(obj),
> len(dataType.fields)))
> 1153 for v, f in zip(obj, dataType.fields):
> -> 1154 _verify_type(v, f.dataType)
> 1155
> 1156
> /mnt/spark/spark/python/pyspark/sql/types.py in _verify_type(obj, dataType)
> 1136 # subclass of them can not be fromInternald in JVM
> 1137 if type(obj) not in _acceptable_types[_type]:
> -> 1138 raise TypeError("%s can not accept object in type %s" %
> (dataType, type(obj)))
> 1139
> 1140 if isinstance(dataType, ArrayType):
> TypeError: DateType can not accept object in type <class 'int'>
> {code}
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