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From "geosmart (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-22678) Schema Exception of SaveAsTable with SparkML Pipeline.transform Result DataFrame
Date Mon, 04 Dec 2017 04:45:00 GMT
geosmart created SPARK-22678:
--------------------------------

             Summary: Schema Exception of SaveAsTable with SparkML Pipeline.transform Result DataFrame 
                 Key: SPARK-22678
                 URL: https://issues.apache.org/jira/browse/SPARK-22678
             Project: Spark
          Issue Type: Bug
          Components: ML
    Affects Versions: 2.2.0
         Environment: Spark-2.2.0 standlone Cluster 

 
I run the app by spark-submit:
```
spark-submit --driver-memory 8g --executor-memory 30G --total-executor-cores  200 --executor-cores 12  Main.py  >preprocess.log &
```

            Reporter: geosmart


I run the app by spark-submit:
```
spark-submit --driver-memory 8g --executor-memory 30G --total-executor-cores  200 --executor-cores 12  Main.py  >preprocess.log &
```

1.	Situatiuon
Input:I have a table of 2500 features to vectoring,only 740000 rows;
Action:do onehotEncoder for category features and minmax or standard scaler for continues features,
Output:a new table with vectoring results(UDT);

2.	Problem
2.1 saveAsTable throws 
Caused by: java.lang.RuntimeException: Couldn't find ALL_FIRST_ATTEMPT_SIGN_1_DATE_ALL_vector#12558 in [cardno#0,ALL_NUM_PAY_BILLS_1_ALL#1,ALL_NUM_PAY_BILLS_1_7D#2,

2.2 I fit the pipeline spend 1 hour, any one knows how to speed up?
When do pipeline transform ,the spark only start a worker process,why not transforming in parallel,the features have no dependency?
and transformed is very slowly ( 10 minutes), no matter how small the input dataset is !



3.	Code
3.1.	Load dataframe 
#feature array from json config  

{code:python}
categoryFeatures, continousFeatures = self.splitFeature(configPath, featureConfig)

log.info("categoryFeatures: {}".format(categoryFeatures))
log.info("continousFeatures: {}".format(continousFeatures))

df = self.spark.table(inputTable)
df = df.select(categoryFeatures + continousFeatures)
{code}


3.2.	 Load or Generate pipeline
{code:python}
def get_onehot_scalar_pipeline(self, categoryFeatures, continousFeatures, df, modelPath, scalerType="minmax"):
    """
    Pipeline:onehot,min-max scalar
    :param categoryFeatures:
    :param df:
    :param modelPath:
    :return:
    """
    pipelineModel = None

    if self.isDebug:
        isLoadModel = os.path.isdir(modelPath)
    else:
        isLoadModel = self.is_path_exist(modelPath)

    if isLoadModel:
        log.info("load pipeline from {}".format(modelPath))
        pipelineModel = PipelineModel.load(modelPath)
    else:
        from pyspark.ml.feature import StringIndexer, OneHotEncoder, StandardScaler
        stages = []

        # OneHotEncoder
        for categoryFeature in categoryFeatures:
            categoryFeatureIndex = categoryFeature + "_index"
            categoryFeatureVector = categoryFeature + "_vector"
            stringIndexer = StringIndexer(inputCol=categoryFeature, outputCol=categoryFeatureIndex, handleInvalid="skip")
            onehotEncoder = OneHotEncoder(inputCol=categoryFeatureIndex, outputCol=categoryFeatureVector,
                                          dropLast=False)
            stages.append(stringIndexer)
            stages.append(onehotEncoder)

        # MinMaxScaler
        assemblerVector = "assembler_vector"
        featureScalar = "scalar_vector"
        assembler = VectorAssembler(inputCols=continousFeatures, outputCol=assemblerVector)

        if scalerType == "standard":
            scaler = StandardScaler(withMean=True, withStd=True, inputCol=assemblerVector, outputCol=featureScalar)
        else:
            scaler = MinMaxScaler(min=0.0, max=1.0, inputCol=assemblerVector, outputCol=featureScalar)
        stages.append(assembler)
        stages.append(scaler)

        t0 = datetime.now()
        log.info("start fit pipeline,stages:{}".format(len(stages)))
        pipelineModel = Pipeline(stages=stages).fit(df)
        tt = datetime.now() - t0
        log.info("done fit pipeline in [{}s]".format(tt.seconds))

        log.info("save pipeline as model {}".format(modelPath))
        self.model_save(pipelineModel, modelPath)
    return pipelineModel

{code}

3.3 Pipeline Transform and Save Result

{code:python}
# load or fit pipeline and transform
pipeline = self.get_onehot_scalar_pipeline(categoryFeatures, continousFeatures, df, modelPath, scalerType)
t0 = datetime.now()
log.info("start pipeline transform,pipeline stages [{}], df size[{}]".format(len(pipeline.stages), df.count()))
df_vector = pipeline.transform(df)
tt = datetime.now() - t0
log.info("done pipeline transform in [{}s]".format(tt.seconds))

# remove temp columns
excludeColumns = []
for categoryFeature in categoryFeatures:
    categoryFeatureIndex = categoryFeature + "_index"
    excludeColumns.append(categoryFeature)
    excludeColumns.append(categoryFeatureIndex)

for continousFeature in continousFeatures:
    excludeColumns.append(continousFeature)

assemblerVector = "assembler_vector"
excludeColumns.append(assemblerVector)

log.info("exclude temp columns")
df_last = df_vector.select([c for c in df_vector.columns if c not in excludeColumns])

log.info("before feature extract...")
df_last.printSchema()

# onehot output SparseVector,convert to multi columns
log.info("start save preprocess vector result as table[{}]".format(outputTable))

# exception happened in saveAsTable
df_last.write.saveAsTable(outputTable)

log.info("done save preprocess vector result as table[{}]".format(outputTable))

{code}


4. Log
detail in ![gist saveAsTable_exception3.log](https://gist.github.com/geosmart/15c6357cf52566439341de6f7edf33e8)


{code:java}
py4j.protocol.Py4JJavaError: An error occurred while calling o3728.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 729.0 failed 4 times, most recent failure: Lost task 0.3 in stage 729.0 (TID 750, 172.31.23.17, executor 0): org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Binding attribute, tree: ALL_FIRST_ATTEMPT_SIGN_1_DATE_ALL_vector#13746
	at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
	at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:88)
	at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1.applyOrElse(BoundAttribute.scala:87)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
	at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$2.apply(TreeNode.scala:267)
	at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:70)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:266)
	at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:256)
	at org.apache.spark.sql.catalyst.expressions.BindReferences$.bindReference(BoundAttribute.scala:87)
	at org.apache.spark.sql.catalyst.expressions.UnsafeProjection$$anonfun$2.apply(Projection.scala:151)
	at org.apache.spark.sql.catalyst.expressions.UnsafeProjection$$anonfun$2.apply(Projection.scala:151)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
	at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
	at scala.collection.AbstractTraversable.map(Traversable.scala:104)
	at org.apache.spark.sql.catalyst.expressions.UnsafeProjection$.create(Projection.scala:151)
	at org.apache.spark.sql.execution.ProjectExec$$anonfun$9.apply(basicPhysicalOperators.scala:74)
	at org.apache.spark.sql.execution.ProjectExec$$anonfun$9.apply(basicPhysicalOperators.scala:73)
	at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:815)
	at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:815)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
	at org.apache.spark.scheduler.Task.run(Task.scala:108)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
	at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.RuntimeException: Couldn't find ALL_FIRST_ATTEMPT_SIGN_1_DATE_ALL_vector#13746 in 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EMPT_SIGN_TO_TODAY_94_ALL#1097,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_TODAY_94_7D#1098,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_TODAY_94_15D#1099,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_TODAY_94_30D#1100,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_TODAY_95_ALL#1101,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_TODAY_95_7D#1102,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_TODAY_95_15D#1103,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_TODAY_95_30D#1104,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_TODAY_96_ALL#1105,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_TODAY_96_7D#1106,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_TODAY_96_15D#1107,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_TODAY_96_30D#1108,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_TODAY_97_ALL#1109,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_TODAY_97_7D#1110,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_TODAY_97_15D#1111,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_TODAY_97_30D#1112,CONSUMERLOAN_DT_FIRST_ATTEMPT_WITHDRAW_TO_TODAY_98_ALL#1113,CONSUMERLOAN_DT_FIRST_ATTEMPT_WITHDRAW_TO_TODAY_98_7D#1114,CONSUMERLOAN_DT_FIRST_ATTEMPT_WITHDRAW_TO_TODAY_98_15D#1115,CONSUMERLOAN_DT_FIRST_ATTEMPT_WITHDRAW_TO_TODAY_98_30D#1116,CONSUMERLOAN_DT_FIRST_SUCCESS_WITHDRAW_TO_TODAY_99_ALL#1117,CONSUMERLOAN_DT_FIRST_SUCCESS_WITHDRAW_TO_TODAY_99_7D#1118,CONSUMERLOAN_DT_FIRST_SUCCESS_WITHDRAW_TO_TODAY_99_15D#1119,CONSUMERLOAN_DT_FIRST_SUCCESS_WITHDRAW_TO_TODAY_99_30D#1120,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_SIGN_100_ALL#1121,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_SIGN_100_7D#1122,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_SIGN_100_15D#1123,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_SIGN_100_30D#1124,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_ATTEMPT_PAY_101_ALL#1125,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_ATTEMPT_PAY_101_7D#1126,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_ATTEMPT_PAY_101_15D#1127,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_ATTEMPT_PAY_101_30D#1128,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_PAY_102_ALL#1129,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_PAY_102_7D#1130,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_PAY_102_15D#1131,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_PAY_102_30D#1132,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_ATTEMPT_WITHDRAW_103_ALL#1133,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_ATTEMPT_WITHDRAW_103_7D#1134,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_ATTEMPT_WITHDRAW_103_15D#1135,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_ATTEMPT_WITHDRAW_103_30D#1136,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_WITHDRAW_104_ALL#1137,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_WITHDRAW_104_7D#1138,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_WITHDRAW_104_15D#1139,CONSUMERLOAN_DT_FIRST_ATTEMPT_SIGN_TO_FIRST_SUCCESS_WITHDRAW_104_30D#1140,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_ATTEMPT_PAY_105_ALL#1141,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_ATTEMPT_PAY_105_7D#1142,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_ATTEMPT_PAY_105_15D#1143,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_ATTEMPT_PAY_105_30D#1144,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_SUCCESS_PAY_106_ALL#1145,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_SUCCESS_PAY_106_7D#1146,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_SUCCESS_PAY_106_15D#1147,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_SUCCESS_PAY_106_30D#1148,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_ATTEMPT_WITHDRAW_107_ALL#1149,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_ATTEMPT_WITHDRAW_107_7D#1150,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_ATTEMPT_WITHDRAW_107_15D#1151,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_ATTEMPT_WITHDRAW_107_30D#1152,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_SUCCESS_WITHDRAW_108_ALL#1153,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_SUCCESS_WITHDRAW_108_7D#1154,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_SUCCESS_WITHDRAW_108_15D#1155,CONSUMERLOAN_DT_FIRST_SUCCESS_SIGN_TO_FIRST_SUCCESS_WITHDRAW_108_30D#1156,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_ATTEMPT_WITHDRAW_109_ALL#1157,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_ATTEMPT_WITHDRAW_109_7D#1158,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_ATTEMPT_WITHDRAW_109_15D#1159,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_ATTEMPT_WITHDRAW_109_30D#1160,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_SUCCESS_WITHDRAW_110_ALL#1161,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_SUCCESS_WITHDRAW_110_7D#1162,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_SUCCESS_WITHDRAW_110_15D#1163,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_SUCCESS_WITHDRAW_110_30D#1164,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_SUCCESS_PAY_111_ALL#1165,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_SUCCESS_PAY_111_7D#1166,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_SUCCESS_PAY_111_15D#1167,CONSUMERLOAN_DT_FIRST_ATTEMPT_PAY_TO_FIRST_SUCCESS_PAY_111_30D#1168,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_FIRST_ATTEMPT_WITHDRAW_112_ALL#1169,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_FIRST_ATTEMPT_WITHDRAW_112_7D#1170,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_FIRST_ATTEMPT_WITHDRAW_112_15D#1171,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_FIRST_ATTEMPT_WITHDRAW_112_30D#1172,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_FIRST_SUCCESS_WITHDRAW_113_ALL#1173,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_FIRST_SUCCESS_WITHDRAW_113_7D#1174,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_FIRST_SUCCESS_WITHDRAW_113_15D#1175,CONSUMERLOAN_DT_FIRST_SUCCESS_PAY_TO_FIRST_SUCCESS_WITHDRAW_113_30D#1176,CONSUMERLOAN_DT_FIRST_ATTEMPT_WITHDRAW_TO_FIRST_SUCCESS_WITHDRAW_114_ALL#1177,CONSUMERLOAN_DT_FIRST_ATTEMPT_WITHDRAW_TO_FIRST_SUCCESS_WITHDRAW_114_7D#1178,CONSUMERLOAN_DT_FIRST_ATTEMPT_WITHDRAW_TO_FIRST_SUCCESS_WITHDRAW_114_15D#1179,CONSUMERLOAN_DT_FIRST_ATTEMPT_WITHDRAW_TO_FIRST_SUCCESS_WITHDRAW_114_30D#1180]
	at scala.sys.package$.error(package.scala:27)
	at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:94)
	at org.apache.spark.sql.catalyst.expressions.BindReferences$$anonfun$bindReference$1$$anonfun$applyOrElse$1.apply(BoundAttribute.scala:88)
	at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
	... 33 more
{code}




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