databricks-connect 9.1 : StreamCorruptedException: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
04-13-2023 06:09 AM
Hello, I'm using databricks-connect 9.1 and I started having issues since last week in all functions that have a "collect()". Everything was working before :
myList = df1.select("id").rdd.flatMap(lambda x: x).collect()
here the error :
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: java.io.StreamCorruptedException: invalid type code: 0E
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1700)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2431)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2355)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2213)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1669)
at java.io.ObjectInputStream.readArray(ObjectInputStream.java:2119)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1657)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2431)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:2355)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:2213)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1669)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:503)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:461)
at org.apache.spark.sql.util.ProtoSerializer.$anonfun$deserializeObject$1(ProtoSerializer.scala:6631)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)
at org.apache.spark.sql.util.ProtoSerializer.deserializeObject(ProtoSerializer.scala:6616)
at com.databricks.service.SparkServiceRPCHandler.execute0(SparkServiceRPCHandler.scala:728)
at com.databricks.service.SparkServiceRPCHandler.$anonfun$executeRPC0$1(SparkServiceRPCHandler.scala:477)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)
at com.databricks.service.SparkServiceRPCHandler.executeRPC0(SparkServiceRPCHandler.scala:372)
at com.databricks.service.SparkServiceRPCHandler$$anon$2.call(SparkServiceRPCHandler.scala:323)
at com.databricks.service.SparkServiceRPCHandler$$anon$2.call(SparkServiceRPCHandler.scala:309)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at com.databricks.service.SparkServiceRPCHandler.$anonfun$executeRPC$1(SparkServiceRPCHandler.scala:359)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)
at com.databricks.service.SparkServiceRPCHandler.executeRPC(SparkServiceRPCHandler.scala:336)
at com.databricks.service.SparkServiceRPCServlet.doPost(SparkServiceRPCServer.scala:167)
at javax.servlet.http.HttpServlet.service(HttpServlet.java:707)
at javax.servlet.http.HttpServlet.service(HttpServlet.java:790)
at org.eclipse.jetty.servlet.ServletHolder.handle(ServletHolder.java:799)
at org.eclipse.jetty.servlet.ServletHandler.doHandle(ServletHandler.java:550)
at org.eclipse.jetty.server.handler.ScopedHandler.nextScope(ScopedHandler.java:190)
at org.eclipse.jetty.servlet.ServletHandler.doScope(ServletHandler.java:501)
at org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:141)
at org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:127)
at org.eclipse.jetty.server.Server.handle(Server.java:516)
at org.eclipse.jetty.server.HttpChannel.lambda$handle$1(HttpChannel.java:388)
at org.eclipse.jetty.server.HttpChannel.dispatch(HttpChannel.java:633)
at org.eclipse.jetty.server.HttpChannel.handle(HttpChannel.java:380)
at org.eclipse.jetty.server.HttpConnection.onFillable(HttpConnection.java:277)
at org.eclipse.jetty.io.AbstractConnection$ReadCallback.succeeded(AbstractConnection.java:311)
at org.eclipse.jetty.io.FillInterest.fillable(FillInterest.java:105)
at org.eclipse.jetty.io.ChannelEndPoint$1.run(ChannelEndPoint.java:104)
at org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.runTask(EatWhatYouKill.java:338)
at org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.doProduce(EatWhatYouKill.java:315)
at org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.tryProduce(EatWhatYouKill.java:173)
at org.eclipse.jetty.util.thread.strategy.EatWhatYouKill.run(EatWhatYouKill.java:131)
at org.eclipse.jetty.util.thread.ReservedThreadExecutor$ReservedThread.run(ReservedThreadExecutor.java:383)
at org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:882)
at org.eclipse.jetty.util.thread.QueuedThreadPool$Runner.run(QueuedThreadPool.java:1036)
at java.lang.Thread.run(Thread.java:750)
I'm using python 3.8.14 with databricks-connect==9.1.24
Have you ever had this issue ? I think it's probably comes for databricks-connect
- Labels:
-
Databricks-connect
-
Invalid Type Code
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
04-15-2023 05:46 PM
@Julien Larcher :
Yes, it is possible that the issue you are experiencing with the StreamCorruptedException is related to Databricks Connect. This error occurs when the data being sent over the network is corrupted or the receiving end is unable to deserialize the received data.
One possible solution is to upgrade to the latest version of Databricks Connect, which at the time of writing is version 10.2. You can try upgrading by running the following command:
pip install databricks-connect==10.2.*
If upgrading Databricks Connect does not resolve the issue, you could also try the following:
- Check if the issue is specific to a particular cluster. If so, try running the same code on a different cluster.
- Check if there are any recent changes made to your code that might have caused this issue.
- Check if there are any recent changes made to your cluster configuration or environment that might have caused this issue.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
04-15-2023 10:17 PM
Hi @Julien Larcher
Thank you for posting your question in our community! We are happy to assist you.
To help us provide you with the most accurate information, could you please take a moment to review the responses and select the one that best answers your question?
This will also help other community members who may have similar questions in the future. Thank you for your participation and let us know if you need any further assistance!

