This is great info. Jackson should only be used once when the file is opened, so this is confusing from that point of view. Is something else using Jackson or initializing an Avro JsonDecoder frequently? There are over 100000 Jackson DeserializationConfig objects.
Another place that parses the schema is in AvroSerialization.java. Does the Hadoop getDeserializer() API method get called once per job, or per record? If this is called more than once per map job, it might explain this. In principle, Jackson is only used by a mapper during initialization. The below indicates that this may not be the case or that something outside of Avro is causing a lot of Jackson JSON parsing. Are you using something that is converting the Avro data to Json form? toString() on most Avro datum objects will do a lot of work with Jackson, for example — but the below are deserializer objects not serializer objects so that is not likely the issue. On 6/1/11 11:34 AM, "ey-chih chow" <[email protected]<mailto:[email protected]>> wrote: We ran jmap on one of our mapper and found the top usage as follows: num #instances #bytes Class description -------------------------------------------------------------------------- 1: 24405 291733256 byte[] 2: 6056 40228984 int[] 3: 388799 19966776 char[] 4: 101779 16284640 org.codehaus.jackson.impl.ReaderBasedParser 5: 369623 11827936 java.lang.String 6: 111059 8769424 java.util.HashMap$Entry[] 7: 204083 8163320 org.codehaus.jackson.impl.JsonReadContext 8: 211374 6763968 java.util.HashMap$Entry 9: 102551 5742856 org.codehaus.jackson.util.TextBuffer 10: 105854 5080992 java.nio.HeapByteBuffer 11: 105821 5079408 java.nio.HeapCharBuffer 12: 104578 5019744 java.util.HashMap 13: 102551 4922448 org.codehaus.jackson.io.IOContext 14: 101782 4885536 org.codehaus.jackson.map.DeserializationConfig 15: 101783 4071320 org.codehaus.jackson.sym.CharsToNameCanonicalizer 16: 101779 4071160 org.codehaus.jackson.map.deser.StdDeserializationContext 17: 101779 4071160 java.io.StringReader 18: 101754 4070160 java.util.HashMap$KeyIterator It looks like Jackson eats up a lot of memory. Our mapper reads in files of the avro format. Does avro use Jackson a lot in reading the avro files? Is there any way to improve this? Thanks. Ey-Chih Chow ________________________________ From: [email protected]<mailto:[email protected]> To: [email protected]<mailto:[email protected]> Date: Tue, 31 May 2011 18:26:23 -0700 Subject: Re: avro object reuse All of those instances are short-lived. If you are running out of memory, its not likely due to object reuse. This tends to cause more CPU time in the garbage collector, but not out of memory conditions. This can be hard to do on a cluster, but grabbing 'jmap –histo' output from a JVM that has a larger-than-expected JVM heap usage can often be used to quickly identify the cause of memory consumption issues. I'm not sure if AvroUtf8InputFormat can safely re-use its instances of Utf8 or not. On 5/31/11 5:40 PM, "ey-chih chow" <[email protected]<mailto:[email protected]>> wrote: I actually looked into Avro code to find out how Avro does object reuse. I looked at AvroUtf8InputFormat and got the following question. Why a new Utf8 object has to be created each time the method next(AvroWrapper<Utf8> key, NullWritable value) is called ? Will this eat up too much memory when we call next(key, value) many times? Since Utf8 is mutable, can we just create one Utf8 object for all the calls to next(key, value)? Will this save memory? Thanks. Ey-Chih Chow ________________________________ From: [email protected]<mailto:[email protected]> To: [email protected]<mailto:[email protected]> Subject: avro object reuse Date: Tue, 31 May 2011 10:38:39 -0700 Hi, We have several mapreduce jobs using avro. They take too much memory when running on production. Can anybody suggest some object reuse techniques to cut down memory usage? Thanks. Ey-Chih Chow
