Jacek Furmankiewicz created CASSANDRA-7303:
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             Summary: OutOfMemoryError during prolonged batch processing
                 Key: CASSANDRA-7303
                 URL: https://issues.apache.org/jira/browse/CASSANDRA-7303
             Project: Cassandra
          Issue Type: Bug
          Components: Core
         Environment: Server: RedHat 6, 64-bit, Oracle JDK 7, Cassandra 2.0.6

Client: Java 7, Astyanax
            Reporter: Jacek Furmankiewicz


We have a prolonged batch processing job. 
It writes a lot of records, every batch mutation creates probably on average 
300-500 columns per row key (with many disparate row keys).

It works fine but within a few hours we get error like this:

ERROR [Thrift:15] 2014-05-24 14:16:20,192 CassandraDaemon.java (line |
|196) Except                                                          |
|ion in thread Thread[Thrift:15,5,main]                               |
|java.lang.OutOfMemoryError: Requested array size exceeds VM limit    |
|at java.util.Arrays.copyOf(Arrays.java:2271)                         |
|at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113)|
|at java.io.ByteArrayOutputStream.ensureCapacity                      |
|(ByteArrayOutputStream.ja                                            |
|va:93)                                                               |
|at java.io.ByteArrayOutputStream.write                               |
|(ByteArrayOutputStream.java:140)                                     |
|at org.apache.thrift.transport.TFramedTransport.write                |
|(TFramedTransport.j                                                  |
|ava:146)                                                             |
|at org.apache.thrift.protocol.TBinaryProtocol.writeBinary            |
|(TBinaryProtoco                                                      |
|l.java:183)                                                          |
|at org.apache.cassandra.thrift.Column$ColumnStandardScheme.write     |
|(Column.                                                             |
|java:678)                                                            |
|at org.apache.cassandra.thrift.Column$ColumnStandardScheme.write     |
|(Column.                                                             |
|java:611)                                                            |
|at org.apache.cassandra.thrift.Column.write(Column.java:538)         |
|at org.apache.cassandra.thrift.ColumnOrSuperColumn                   |
|$ColumnOrSuperColumnSt                                               |
|andardScheme.write(ColumnOrSuperColumn.java:673)                     |
|at org.apache.cassandra.thrift.ColumnOrSuperColumn                   |
|$ColumnOrSuperColumnSt                                               |
|andardScheme.write(ColumnOrSuperColumn.java:607)                     |
|at org.apache.cassandra.thrift.ColumnOrSuperColumn.write             |
|(ColumnOrSuperCo                                                     |
|lumn.java:517)                                                       |
|at org.apache.cassandra.thrift.Cassandra$get_slice_result            |
|$get_slice_resu                                                      |
|ltStandardScheme.write(Cassandra.java:11682)                         |
|at org.apache.cassandra.thrift.Cassandra$get_slice_result            |
|$get_slice_resu                                                      |
|ltStandardScheme.write(Cassandra.java:11603)                         |
|at org.apache.cassandra.thrift.Cassandra

The server already has 16 GB heap, which we hear is the max Cassandra can run 
with. The writes are heavily multi-threaded from a single server.

The jist of the issue is that Cassandra should not crash with OOM when under 
heavy load. It is  OK  to slow down, even maybe start throwing operation 
timeout exceptions, etc.

But to just crash in the middle of the processing should not be allowed.

is there any internal monitoring of heap usage in Cassandra where it could 
detect that it is getting close to the heap limit and start throttling the 
incoming requests to avoid this type of error?

Thanks




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