问题
When I try to collect data from Spark dataframe, I get an error stating
"java.lang.IllegalArgumentException: requirement failed: Decimal precision 39 exceeds max precision 38".
All the data which is in Spark dataframe is from Oracle database, where I believe decimal precision is <38. Is there any way I can achieve this without modifying the data?
# Load required table into memory from Oracle database
df <- loadDF(sqlContext, source = "jdbc", url = "jdbc:oracle:thin:usr/pass@url.com:1521" , dbtable = "TBL_NM")
RawData <- df %>%
filter(DT_Column > DATE(‘2015-01-01’))
RawData <- as.data.frame(RawData)
Gives error
Below is the stacktrace:
WARN TaskSetManager: Lost task 1.0 in stage 0.0 (TID 1, 10...***, executor 0): java.lang.IllegalArgumentException: requirement failed: Decimal precision 39 exceeds max precision 38 at scala.Predef$.require(Predef.scala:224) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:113) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:426) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$3$$anonfun$9.apply(JdbcUtils.scala:337) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$3$$anonfun$9.apply(JdbcUtils.scala:337) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$nullSafeConvert(JdbcUtils.scala:438) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$3.apply(JdbcUtils.scala:337) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$org$apache$spark$sql$execution$datasources$jdbc$JdbcUtils$$makeGetter$3.apply(JdbcUtils.scala:335) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:286) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:268) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231) at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:99) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745)
Please suggest any solution. Thank you.
来源：https://stackoverflow.com/questions/44130460/spark-error-decimal-precision-39-exceeds-max-precision-38