Miroslav Spehar created SPARK-20162:
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Summary: Reading data from MySQL - Cannot up cast from
decimal(30,6) to decimal(38,18)
Key: SPARK-20162
URL: https://issues.apache.org/jira/browse/SPARK-20162
Project: Spark
Issue Type: Bug
Components: Spark Core
Affects Versions: 2.1.0
Reporter: Miroslav Spehar
Priority: Minor
While reading data from MySQL, type conversion doesn't work for Decimal type
when the decimal in database is of lower precision/scale than the one spark
expects.
Error:
Exception in thread "main" org.apache.spark.sql.AnalysisException: Cannot up
cast `DECIMAL_AMOUNT` from decimal(30,6) to decimal(38,18) as it may truncate
The type path of the target object is:
- field (class: "org.apache.spark.sql.types.Decimal", name: "DECIMAL_AMOUNT")
- root class: "com.misp.spark.Structure"
You can either add an explicit cast to the input data or choose a higher
precision type of the field in the target object;
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$.org$apache$spark$sql$catalyst$analysis$Analyzer$ResolveUpCast$$fail(Analyzer.scala:2119)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$$anonfun$apply$34$$anonfun$applyOrElse$14.applyOrElse(Analyzer.scala:2141)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$$anonfun$apply$34$$anonfun$applyOrElse$14.applyOrElse(Analyzer.scala:2136)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:288)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:287)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$transformDown$1.apply(TreeNode.scala:293)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5$$anonfun$apply$11.apply(TreeNode.scala:360)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
at
scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
at scala.collection.immutable.List.map(List.scala:285)
at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$5.apply(TreeNode.scala:358)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformChildren(TreeNode.scala:329)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:293)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionDown$1(QueryPlan.scala:248)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.org$apache$spark$sql$catalyst$plans$QueryPlan$$recursiveTransform$1(QueryPlan.scala:258)
at
org.apache.spark.sql.catalyst.plans.QueryPlan$$anonfun$6.apply(QueryPlan.scala:267)
at
org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:188)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsDown(QueryPlan.scala:267)
at
org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressions(QueryPlan.scala:236)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$$anonfun$apply$34.applyOrElse(Analyzer.scala:2136)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$$anonfun$apply$34.applyOrElse(Analyzer.scala:2132)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan$$anonfun$resolveOperators$1.apply(LogicalPlan.scala:61)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveOperators(LogicalPlan.scala:60)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$.apply(Analyzer.scala:2132)
at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveUpCast$.apply(Analyzer.scala:2117)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:85)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1$$anonfun$apply$1.apply(RuleExecutor.scala:82)
at
scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:124)
at scala.collection.immutable.List.foldLeft(List.scala:84)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:82)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$execute$1.apply(RuleExecutor.scala:74)
at scala.collection.immutable.List.foreach(List.scala:381)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:74)
at
org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.resolveAndBind(ExpressionEncoder.scala:258)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:209)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:167)
at org.apache.spark.sql.Dataset$.apply(Dataset.scala:58)
at org.apache.spark.sql.Dataset.as(Dataset.scala:376)
at com.misp.spark.CalculationEngine$.main(CalculationEngine.scala:109)
at com.misp.spark.CalculationEngine.main(CalculationEngine.scala)
Process finished with exit code 1
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