|00000006|[0.0, 2.0721931, |[4.0]| Caused by: java.lang.UnsupportedOperationException: empty.reduceLeft 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Final stage: ResultStage 6 in () $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239) windowSpec = Window.partitionBy(df['id']).orderBy(df_Broadcast['id']) windowSp. in () Sorry, those notebooks have been updated with some sort of script to prepare the Colab with Java, I wasnt aware of that. from com.yahoo.ml.caffe.DataSource import DataSource at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381) 16/04/27 10:44:34 INFO scheduler.DAGScheduler: ResultStage 4 (collect at CaffeOnSpark.scala:127) finished in 0.084 s 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Submitting 1 missing tasks from ResultStage 4 (MapPartitionsRDD[14] at map at CaffeOnSpark.scala:116) at Making location easier for developers with new data primitives, Stop requiring only one assertion per unit test: Multiple assertions are fine, Mobile app infrastructure being decommissioned. df_errors = df_all.filter( (col("foo_code") == lit('FAIL')) We require the UDF to return two values: The output and an error code. at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237) next step on music theory as a guitar player, Correct handling of negative chapter numbers. dl_train_source = DataSource(sc).getSource(cfg,True) How to control Windows 10 via Linux terminal? I run COLAB set-up code without any problem. All rights reserved. 16/04/27 10:44:34 INFO storage.BlockManagerInfo: Added rdd_12_0 on disk on 16/04/27 10:44:34 INFO spark.SparkContext: Starting job: reduce at 16/04/27 10:44:34 INFO spark.SparkContext: Created broadcast 6 from at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055) at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) Thank you for your suggestions :), @mriduljain after the training, when i run below code in notebook: cfg.clusterSize = 1 from com.yahoo.ml.caffe.RegisterContext import 16/04/27 10:44:34 INFO storage.MemoryStore: Block broadcast_5_piece0 stored as bytes in memory (estimated size 2.1 KB, free 25.9 KB) from pyspark import SparkConf,SparkContext Start your " pyspark " shell from $SPARK_HOME\bin folder and enter the pyspark command. from ResultStage 6 (MapPartitionsRDD[17] at mapPartitions at TungstenAggregate(key=[], functions=[(count(1),mode=Final,isDistinct=false)], output=[count#30L]) only showing top 10 rows, @dejunzhang I tried to reproduce your earlier problem (i.e local lmdbs) but couldn't :(. at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) Py4JJavaError: An error occurred while calling o864.features. : org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree: at org.apache.spark.rdd.RDD.partitions(RDD.scala:237) at py4j.Gateway.invoke(Gateway.java:259) i changed the proto file path like below: File "/home/atlas/work/caffe_spark/CaffeOnSpark-master/caffe-grid/target/caffeonsparkpythonapi.zip/com/yahoo/ml/caffe/CaffeOnSpark.py", line 45, in features File "/home/atlas/work/caffe_spark/3rdparty/spark-1.6.0-bin-hadoop2.6/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py", line 813, in call haha_____The error in my case was: PySpark was running python 2.7 from my environment's default library.. What is the best way to show results of a multiple-choice quiz where multiple options may be right? at com.yahoo.ml.caffe.CaffeOnSpark$$anonfun$7.apply(CaffeOnSpark.scala:199) at scala.collection.AbstractIterator.reduceLeft(Iterator.scala:1157) at py4j.Gateway.invoke(Gateway.java:259) IPYTHON=1 pyspark --master yarn at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) It has to be 8. from com.yahoo.ml.caffe.RegisterContext import registerContext,registerSQLContext import numpy as np # Example data d_np = pd.DataFrame ( {'int_arrays': [ [1,2,3], [4,5,6]]}) 248 self.write_format_data(format_dict, md_dict) 404 page not found when running firebase deploy, SequelizeDatabaseError: column does not exist (Postgresql), Remove action bar shadow programmatically, AWS Glue predicate push down condition has no effect, Filter pyspark dataframe if contains a list of strings, 'RDD' object has no attribute '_jdf' pyspark RDD, Spark Python error "FileNotFoundError: [WinError 2] The system cannot find the file specified", How to change case of whole pyspark dataframe to lower or upper. How can I get a huge Saturn-like ringed moon in the sky? pushd ${CAFFE_ON_SPARK}/data/ 484 p.begin_group(1, '<'), @mriduljain @anfeng yes. That's maybe 26 to 30GB getting used vs node memory of 16 GB. and get : Advance note: Audio was bad because I was traveling. missing parents 43 def deco(_a, *_kw): at com.yahoo.ml.caffe.CaffeOnSpark$$anonfun$7.apply(CaffeOnSpark.scala:191) I am using PROCESS by Johnson-Neyman to analyze my Moderator model. at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) Hope this can be of any use to other looking for a similar error out in the web. Hi All, My question is about modeling time series using LSTM (Long-Short-Term-Memory). TypeError Traceback (most recent call last) at org.apache.spark.scheduler.Task.run(Task.scala:89) 480 if getattr(klass, 'repr', None) not in _baseclass_reprs: 4.3. py4j.protocol Py4J Protocol . 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Parents of final stage: List() at org.apache.spark.SparkContext.addFile(SparkContext.scala:1368) Unix to verify file has no content and empty lines, BASH: can grep on command line, but not in script, Safari on iPad occasionally doesn't recognize ASP.NET postback links, anchor tag not working in safari (ios) for iPhone/iPod Touch/iPad. |00000008|[0.8896437, 0.478|[5.0]| at org.apache.spark.sql.execution.Exchange$$anonfun$doExecute$1.apply(Exchange.scala:248) at org.apache.spark.rdd.RDD.partitions(RDD.scala:237) By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. This is caught by a fatal assertion . at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35) @anfeng I ran into the same question that when executing "cos.features(data_source)", it failed with error message. 307 "An error occurred while calling {0}{1}{2}.\n". at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) CaffeOnSpark.scala:127) with 1 output partitions at org.apache.spark.SparkContext.runJob(SparkContext.scala:1952) Sign in at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) First, please use the latest release. +- InMemoryColumnarTableScan InMemoryRelation [SampleID#74,ip1#75,label#76], true, 10000, StorageLevel(true, false, false, false, 1), ConvertToUnsafe, None, Caused by: org.apache.spark.SparkException: addFile does not support local directories when not running local mode. at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832) 46 except py4j.protocol.Py4JJavaError as e: 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Submitting ResultStage 4 (MapPartitionsRDD[14] at map at CaffeOnSpark.scala:116), which has no missing parents PySpark is an interface for Apache Spark in Python. DataFrame show() . You need more memory to perform the operations and avoid the OOM error. 16/04/27 10:44:34 INFO caffe.CaffeOnSpark: rank = 0, address = null, The first step is to read in the data. Another problem happened that: Requested # of executors: 1 actual # of executors:2. File "/home/atlas/work/caffe_spark/CaffeOnSpark-master/caffe-grid/target/caffeonsparkpythonapi.zip/com/yahoo/ml/caffe/ConversionUtil.py", line 619, in callJavaMethod Related. But while running the 479 type_pprinters=self.type_printers, at Sign up for a free GitHub account to open an issue and contact its maintainers and the community. --> 362 return _default_pprint(obj, self, cycle) Asking for help, clarification, or responding to other answers. at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) I have already tried gradient PCR and changing extension time; however Hi, I am trying to figure out which test would be most appropriate to run for the following question: Is there a difference in task blood pressure between smokers and non-smokers? at com.yahoo.ml.caffe.CaffeOnSpark$$anonfun$7.apply(CaffeOnSpark.scala:199) 16/04/27 10:44:34 INFO caffe.LmdbRDD: 1 LMDB RDD partitions at org.apache.spark.rdd.RDD$$anonfun$, $1.apply(RDD.scala:939) How to set up LSTM for Time Series Forecasting? 16/04/27 10:44:34 INFO scheduler.TaskSetManager: Starting task 0.0 in stage 4.0 (TID 10, sweet, partition 0,PROCESS_LOCAL, 2169 bytes) at java.lang.Thread.run(Thread.java:745), Driver stacktrace: However the PCR is not working. at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) at org.apache.spark.sql.execution.Exchange$$anonfun$doExecute$1.apply(Exchange.scala:254) Out[13]: --------------------------------------------------------------------------- at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239) --> 813 answer, self.gateway_client, self.target_id, self.name) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237) Spark NLP version 2.5.1 java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799) 16/04/27 14:41:25 INFO caffe.DataSource$: Source data layer:1 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) cfg.outputFormat = 'json' * at com.yahoo.ml.caffe.LmdbRDD.getPartitions(LmdbRDD.scala:44)* --py-files ${CAFFE_ON_SPARK}/caffe-grid/target/caffeonsparkpythonapi.zip stage 6.0 (TID 13, sweet, partition 0,PROCESS_LOCAL, 1992 bytes) at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35) 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Got job 5 (collect at CaffeOnSpark.scala:155) with 1 output partitions I0428 10:06:48.288913 3137 sgd_solver.cpp:273] Snapshotting solver state to binary proto file mnist_lenet_iter_10000.solverstate stage 4.0 (TID 10) in 84 ms on sweet (1/1) +- InMemoryColumnarTableScan InMemoryRelation [SampleID#74,ip1#75,label#76], true, 10000, StorageLevel(true, false, false, false, 1), ConvertToUnsafe, None, Caused by: org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree: registerSQLContext(sqlContext) Subscribe to RSS Feed; Mark Question as New; Mark Question as Read; Float this Question for Current User; Bookmark; Subscribe; broadcast at DAGScheduler.scala:1006 : org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree: extracted_df.show(10) 159 def write_format_data(self, format_dict, md_dict=None): /usr/lib/python2.7/dist-packages/IPython/core/formatters.pyc in format(self, obj, include, exclude) Does the 0m elevation height of a Digital Elevation Model (Copernicus DEM) correspond to mean sea level? at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761) 812 return_value = get_return_value( Our partners will collect data and use cookies for ad personalization and measurement. Hello guys,I am able to connect to snowflake using python JDBC driver but not with pyspark in jupyter notebook?Already confirmed correctness of my username and password. However, when the size of the memory reference offset needed is greater than 2K, VLRL cannot be used. what about the path to your data in lenet_memory_train_test.prototxt? at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237) Then inside the calc_model function, I write out the parquet table. 37 more. 815 for temp_arg in temp_args: /home/atlas/work/caffe_spark/3rdparty/spark-1.6.0-bin-hadoop2.6/python/pyspark/sql/utils.pyc in deco(_a, *_kw) at scala.collection.TraversableOnce$class.reduce(TraversableOnce.scala:195) to your account. at com.yahoo.ml.caffe.CaffeOnSpark$$anonfun$7.apply(CaffeOnSpark.scala:191) I0428 10:06:41.777799 3137 sgd_solver.cpp:106] Iteration 9900, lr = 0.00596843 at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) In [31]: lr_raw_source = DataSource(sc).getSource(cfg,False) 16/04/27 10:44:34 INFO cluster.YarnScheduler: Removed TaskSet 4.0, whose 16/04/28 10:06:48 INFO caffe.CaffeProcessor: Snapshot saving into files at iteration #10000 at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620) at scala.collection.TraversableOnce$class.reduce(TraversableOnce.scala:195) I run 1.SparkNLP_Basics.ipynb notebook on COLAB. 47 s = e.java_exception.toString(), /home/atlas/work/caffe_spark/3rdparty/spark-1.6.0-bin-hadoop2.6/python/lib/py4j-0.9-src.zip/py4j/protocol.py 16/04/27 10:44:34 INFO scheduler.DAGScheduler: ResultStage 6 (reduce at CaffeOnSpark.scala:205) failed in 0.117 s, Py4JJavaError Traceback (most recent call last) 16/04/27 10:44:34 INFO storage.MemoryStore: Block broadcast_8_piece0 How can identify the root cause of this Py4JJavaError and fix it to prevent constant crashing of the workers? cfg.isFeature=True Error code: 390100, Message: Incorrect username or password was specified : org.apache.spark.SparkException: Job aborted due to stage failure: Task File "/home/atlas/work/caffe_spark/CaffeOnSpark-master/caffe-grid/src/main/python/examples/MultiClassLogisticRegression.py", line 36, in Can "it's down to him to fix the machine" and "it's up to him to fix the machine"? thanks a lot. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. at We provide programming data of 20 most popular languages, hope to help you! org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588) 310 raise Py4JError(, Py4JJavaError: An error occurred while calling o2122.train. On Tue, Apr 26, 2016 at 8:07 PM, dejunzhang notifications@github.com 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Got job 5 (collect at Jaa is throwing an exception. : net.snowflake.client.jdbc.SnowflakeSQLException: JDBC driver not able to connect to Snowflake. registerSQLContext(sqlContext) source: "/home/atlas/work/caffe_spark/CaffeOnSpark-master/data/train.txt". at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) from com.yahoo.ml.caffe.CaffeOnSpark import CaffeOnSpark empty.reduceLeft at org.apache.spark.rdd.RDD.withScope(RDD.scala:316) at Thank you. 16/04/28 10:06:48 INFO executor.Executor: Running task 0.0 in stage 13.0 (TID 13) In order to correct it do the following. at org.apache.spark.api.python.PythonRunner$$, $1.read(PythonRunner.scala:421) source: "file:/Users/mridul/bigml/demodl/mnist_train_lmdb" I am using Hortonworks Sandbox VMware 2.6 and SSH into the Terminal to start pyspark: su - hive -c pyspark - 178241. It is now read-only. 43 def deco(_a, *_kw): Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type. The piece above runs fine, However, when I run the code below: parsedData.map(lambda lp: lp.features).mean(). values in memory (estimated size 2.6 KB, free 28.9 KB) 16/04/27 10:44:34 ERROR scheduler.TaskSetManager: Task 0 in stage 6.0 OpenJDK 64-Bit Server VM (build 25.252-b09, mixed mode). 9 . Py4JJavaError: An error occurred while calling z:com.johnsnowlabs.nlp.pretrained.PythonResourceDownloader.downloadPipeline. Spark m3eecexj 2021-05-27 (208) 2021-05-27 . I already shared the pyspark and spark-nlp version before: Spark NLP version 2.5.1 Apache Spark version: 2.4.4. 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Submitting ResultStage 5 (MapPartitionsRDD[16] at map at CaffeOnSpark.scala:149), which has no missing parents --conf spark.cores.max=1 at cfg.protoFile='/Users/afeng/dev/ml/CaffeOnSpark/data/lenet_memory_solver.prototxt' So I fell back to our original setup commands. 818 raise, /home/atlas/work/caffe_spark/CaffeOnSpark-master/data/com/yahoo/ml/caffe/ConversionUtil.py Apache Spark version: 2.4.4, The Java version: What is the effect of cycling on weight loss? No Seasonality (? 16/04/27 10:44:34 INFO storage.MemoryStore: Block broadcast_7 stored as values in memory (estimated size 2.6 KB, free 28.9 KB) scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) registerContext,registerSQLContext at scala.collection.TraversableOnce$, $class.toBuffer(TraversableOnce.scala:302) at com.yahoo.ml.caffe.CaffeOnSpark$$anonfun$7.apply(CaffeOnSpark.scala:191) hello everyone I am working on PySpark Python and I have mentioned the code and getting some issue, I am wondering if someone knows about the following issue? ---> 45 return f(_a, *_kw) I0428 10:06:48.291647 3137 solver.cpp:459] Snapshotting to binary proto file mnist_lenet_iter_10000.caffemodel at scala.Option.getOrElse(Option.scala:120) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237) +--------+--------------------+-----+ 33 def test(self,test_source): /home/atlas/work/caffe_spark/CaffeOnSpark-master/data/com/yahoo/ml/caffe/ConversionUtil.py in call(self, _args) Hi, I am trying to construct a multi-layer fibril structure from a single layer in PyMol by translating the layer along the fibril axis. Well occasionally send you account related emails. at org.apache.spark.SparkContext.runJob(SparkContext.scala:1952) 30 """ --py-files ${CAFFE_ON_SPARK}/caffe-grid/target/caffeonsparkpythonapi.zip 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Submitting 1 missing tasks 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Submitting ResultStage 6 (MapPartitionsRDD[17] at mapPartitions at CaffeOnSpark.scala:190), which has no missing parents I think the problem is in the way I am using the Hi everyone, I am conducting research for my Master's thesis. I have tried decreasing memory limits but all the same results. (MapPartitionsRDD[14] at map at CaffeOnSpark.scala:116), which has no Do US public school students have a First Amendment right to be able to perform sacred music? Solution 1. 154 # FIXME: log the exception, /usr/lib/python2.7/dist-packages/IPython/core/formatters.pyc in call(self, obj) try catch . So, I have been trying to run a pACYC PCR which will be used later on for a Gibson Assembly. Is there anywhere in the code you are mentioning the hostname, "dclvmsbigdmd01"? cfg.lmdb_partitions=cfg.clusterSize. Spark m3eecexj 2021-05-27 (208) 2021-05-27 . You signed in with another tab or window. sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) FROM HumanResources_Employee""") myresults.show () As you can see from the results below, pyspark isn't able to recognize the number '20'. the size of data.mdb is 7KB, and data.mdb.filepart is about 60316 KB. --files ${CAFFE_ON_SPARK}/data/caffe/_caffe.so,${CAFFE_ON_SPARK}/data/lenet_memory_solver.prototxt,${CAFFE_ON_SPARK}/data/lenet_memory_train_test.prototxt Data Science Stack Exchange is a question and answer site for Data science professionals, Machine Learning specialists, and those interested in learning more about the field. "${CAFFE_ON_SPARK}/caffe-grid/target/caffe-grid-0.1-SNAPSHOT-jar-with-dependencies.jar", Then run examples as below, there is a error appeared for the last line: -devices 1 -outputFormat json -clusterSize 1" 16/04/27 10:44:34 INFO storage.BlockManagerInfo: Added broadcast_6_piece0 16/04/27 10:44:34 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 6.0 (TID 12, sweet): java.lang.UnsupportedOperationException: empty.reduceLeft 29 :param DataSource: the source for training data at org.apache.spark.api.python.BasePythonRunner$, $class.foreach(Iterator.scala:893) 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Final stage: ResultStage 4 (collect at CaffeOnSpark.scala:127) +- TungstenExchange SinglePartition, None at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) Ok I updated all the notebooks.. looks like installing jdk 1.8 through local script is not working all the time. At that moment, from the executor log, we can see that the model is trained successfully. ----> 1 cos.train(dl_train_source). Py4JJavaError It is the most common exception while working with the UDF. So please make sure you installed spark-nlp==3.1.1 and have your Spark NLP started as follows: (This will take care of everything so no need to have that SparkSession snippet in your code) |00000005|[0.0, 0.0, 2.0688|[1.0]| The text was updated successfully, but these errors were encountered: I am not sure where is that notebook so I can take a look at it, but this error is about the JAVA version not being supported by Apache Spark. 16/04/27 10:44:34 INFO storage.MemoryStore: Block broadcast_6 stored as at py4j.commands.CallCommand.execute(CallCommand.java:79) in memory on sweet:46000 (size: 2.1 KB, free: 511.5 MB) cfg.clusterSize = 1 sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) the problem is solved. at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640) in memory on sweet:46000 (size: 2.2 KB, free: 511.5 MB) 16/04/27 10:44:34 INFO scheduler.DAGScheduler: Submitting ResultStage 5 at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239) IPYTHON=1 pyspark --master yarn sweet:46000 (size: 26.0 B) --py-files ${CAFFE_ON_SPARK}/caffe-grid/target/caffeonsparkpythonapi.zip 16/04/28 10:06:48 INFO caffe.FSUtils$: destination file:file:///tmp/mnist_lenet_iter_10000.caffemodel it means that the local file can be accessed during training, but for feature extraction, it was not. at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419) at scala.Option.getOrElse(Option.scala:120) After around 180k parquet tables written to Hadoop, the python worker unexpectedly crashes due to EOFException in Java. An Py4JJavaError happened when follow the python instructions. 16/04/28 10:06:48 INFO executor.Executor: Finished task 0.0 in stage 12.0 (TID 12). I'm running a logistic regression with about 200k observations, in which there is one binary predictor where out of the 200k observations there is only 4 occurrence of "1". the error message is : at scala.Option.getOrElse(Option.scala:120) ,JobTitle. 16/04/27 10:44:34 INFO storage.BlockManagerInfo: Added broadcast_6_piece0 in memory on sweet:46000 (size: 221.0 B, free: 511.5 MB) in call(self, _args) 814 for i in self.syms: 815 try: --> 816 return Use MathJax to format equations. https://github.com/yahoo/CaffeOnSpark/wiki/GetStarted_python cfg.protoFile='/Users/afeng/dev/ml/CaffeOnSpark/data/lenet_memory_solver.prototxt' : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 6.0 failed 4 times, most recent failure: Lost task 0.3 in stage 6.0 (TID 15, sweet): java.lang.UnsupportedOperationException: empty.reduceLeft Spark Notebook used below code %%pyspark from pyspark.sql import SparkSession, Row import pydeequ spark = (SparkSession.builder.config("spark.jars.packages", pydeequ.deequ_maven_coord)
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pyspark catch py4jjavaerror