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From Yong Zhang <java8...@hotmail.com>
Subject RE: Strange AVRO 1.7.4 exception
Date Fri, 22 Jan 2016 18:19:39 GMT
I modify the DirectBinaryDecorder class to add the following line from 116, at runtime to dump
more information about it:if (((n >>> 1 ^ -(n & 1)) < 0){ System.out.println("Got
((n >>> 1 ^ -(n & 1)) = " + ((n >>> 1 ^ -(n & 1))); System.out.println("And
b = " + b); System.out.println("And shift = " + shift); System.out.println("And n = " + n);
Here is the output:
Got ((n >>> 1) ^ -(n & 1)) = -51
And b = 101
And shift = 0
And n = 101
Not sure what do these values mean, but does it help to prove this is a bug?
From: java8964@hotmail.com
To: user@avro.apache.org
Subject: RE: Strange AVRO 1.7.4 exception
Date: Fri, 22 Jan 2016 11:48:07 -0500

Based on AVRO-1198, when a negative value return in this case, it means the the data is Malformed,
and this JIRA even patched a message to show it in the Exception.
But in my case:
The avro data is NOT malformed. Why? I can query the whole ready to merge data set in the
Hive without any issue, even for the complained records.In my case, the real runtime object
is "DirectBinaryDecoder", as you can see the stacktrace, doReadBytes method indeed point to
this class.So the ReadInt() method returns "-51" in this case, must be from DirectBinaryDecoder
class, which I list here:           https://github.com/apache/avro/blob/release-1.7.4/lang/java/avro/src/main/java/org/apache/avro/io/DirectBinaryDecoder.java
          starting from line 97, but I really don't know why in my case, it return "-51".I
tested with AVRO 1.7.7 (The latest release of 1.7.x), the same problem still happens.
From: java8964@hotmail.com
To: user@avro.apache.org
Subject: RE: Strange AVRO 1.7.4 exception
Date: Fri, 22 Jan 2016 11:03:43 -0500

With lots of time debugging this, I found out some interested facts, and want to know if any
one can provide more information related to this.
In our AVRO schema, if the "list_id", which is a UUID, contain the following characters "3a3ffb10be8b11e3977ad4ae5284344f",
that record will cause this exception.
In this case, if you check the following Avro class: BinaryDecoder.java, from here:
The above link is pointing to release 1.7.4, and starting from line 259:
int length = readInt();Utf8 result = (old != null ? old : new Utf8());    result.setByteLength(length);
   if (0 != length) {      doReadBytes(result.getBytes(), 0, length);    }In this case when
the exception happens, the length in fact is "-51", which is calculated from method "readInt()",
causing IndexOutOfBoundsException.
I am not very understanding how the readInt() method works, but can anyone share any idea
how this method will return a negative value under what kind of cases?

From: java8964@hotmail.com
To: user@avro.apache.org
Subject: Strange AVRO 1.7.4 exception
Date: Thu, 21 Jan 2016 10:53:38 -0500

Hi, AVRO gurus:
I am facing a strange case in the AVRO right now, and hope someone here can at least give
me some hints or a direction debugging it.
Our production cluster is CENTOS 6.5 (2.6.32-358.14.1.el6.x86_64), running IBM BigInsight
V3.0.0.2. In Apache term, it is Hadoop 2.2.0 with MRV1(no yarn), and comes with AVRO 1.7.4,
running with IBM J9 VM (build 2.7, JRE 1.7.0 Linux amd64-64 Compressed References 20140515_199835
(JIT enabled, AOT enabled). Not sure if the JDK matters, but it is NOT Oracle JVM.
We have a ETL implemented in a chain of MR jobs. In one MR job, it is going to merge 2 sets
of AVRO data. Dataset1 is in HDFS location A, and Dataset2 is in HDFS location B, and both
contains the AVRO records binding to the same AVRO schema. The record contains an unique id
field, and a timestamp field. The MR job is to merge the records based on the ID, and use
the later timestamp record to replace previous timestamp record, and omit the final AVRO record
out. Very straightforward.
Now we faced a problem that one reducer keeps failing with the following stacktrace on JobTracker:
	at java.io.ByteArrayInputStream.read(ByteArrayInputStream.java:191)
	at java.io.DataInputStream.read(DataInputStream.java:160)
	at org.apache.avro.io.DirectBinaryDecoder.doReadBytes(DirectBinaryDecoder.java:184)
	at org.apache.avro.io.BinaryDecoder.readString(BinaryDecoder.java:263)
	at org.apache.avro.io.ValidatingDecoder.readString(ValidatingDecoder.java:107)
	at org.apache.avro.generic.GenericDatumReader.readString(GenericDatumReader.java:348)
	at org.apache.avro.reflect.ReflectDatumReader.readString(ReflectDatumReader.java:143)
	at org.apache.avro.reflect.ReflectDatumReader.readString(ReflectDatumReader.java:125)
	at org.apache.avro.reflect.ReflectDatumReader.readString(ReflectDatumReader.java:121)
	at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:154)
	at org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:177)
	at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:148)
	at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:139)
	at org.apache.avro.hadoop.io.AvroDeserializer.deserialize(AvroDeserializer.java:108)
	at org.apache.avro.hadoop.io.AvroDeserializer.deserialize(AvroDeserializer.java:48)
	at org.apache.hadoop.mapreduce.task.ReduceContextImpl.nextKeyValue(ReduceContextImpl.java:142)
	at org.apache.hadoop.mapreduce.task.ReduceContextImpl.nextKey(ReduceContextImpl.java:117)
	at org.apache.hadoop.mapreduce.lib.reduce.WrappedReducer$Context.nextKey(WrappedReducer.java:297)
	at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:165)
	at org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:652)
	at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:420)
	at org.apache.hadoop.mapred.Child$4.run(Child.java:255)
	at java.security.AccessController.doPrivileged(AccessController.java:366)
	at javax.security.auth.Subject.doAs(Subject.java:572)
	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1502)
	at org.apache.hadoop.mapred.Child.main(Child.java:249)
Here is the my Mapper and Reducer methods:Mapper:public void map(AvroKey<SpecificRecord>
key, NullWritable value, Context context) throws IOException, InterruptedException Reducer:protected
void reduce(CustomPartitionKeyClass key, Iterable<AvroValue<SpecificRecord>> values,
Context context) throws IOException, InterruptedException 
What bother me are the following facts:1) All the mappers finish without error2) Most of the
reducers finish without error, but one reducer keeps failing with the above error.3) It looks
like caused by the data? But keep in mind that all the avro records passed the mapper side,
but failed in one reducer. 4) From the stacktrace, it looks like our reducer code was NOT
invoked yet, but failed before that. So my guess is that all the AVRO records pass through
the mapper side, but AVRO complains the intermediate result generated by the one mapper? In
my understanding, that will be a Sequence file generated by Hadoop, and value part will be
the AVRO bytes. Is the above error meaning that AVRO cannot deserialize the value part from
the sequence file?5) Our ETL run fine for more than one year, but suddenly got this error
starting from one day, and kept getting this problem after that. 6) If it helps, here is the
schema for the avro record:{
    "namespace" : "company name",
    "type" : "record",
    "name" : "Lists",
    "fields" : [
        {"name" : "account_id", "type" : "long"},
        {"name" : "list_id", "type" : "string"},
        {"name" : "sequence_id", "type" : ["int", "null"]} ,
        {"name" : "name", "type" : ["string", "null"]},
        {"name" : "state", "type" : ["string", "null"]},
        {"name" : "description", "type" : ["string", "null"]},
        {"name" : "dynamic_filtered_list", "type" : ["int", "null"]},
        {"name" : "filter_criteria", "type" : ["string", "null"]},
        {"name" : "created_at", "type" : ["long", "null"]},
        {"name" : "updated_at", "type" : ["long", "null"]},
        {"name" : "deleted_at", "type" : ["long", "null"]},
        {"name" : "favorite", "type" : ["int", "null"]},
        {"name" : "delta", "type" : ["boolean", "null"]},
            "name" : "list_memberships", "type" : {
                "type" : "array", "items" : {
                    "name" : "ListMembership", "type" : "record",
                    "fields" : [
                        {"name" : "channel_id", "type" : "string"},
                        {"name" : "created_at", "type" : ["long", "null"]},
                        {"name" : "created_source", "type" : ["string", "null"]},
                        {"name" : "deleted_at", "type" : ["long", "null"]},
                        {"name" : "sequence_id", "type" : ["long", "null"]}
What I am looking for is that someone can help me understand what could cause this problem
in the reducer side? From all the facts, it points to the data. As whole thing works for more
than one year, but suddenly cannot merge the new coming data. But what kind of data cause
the above error, or how should I debug this issue? The data generated as AVRO records just
look fine and read in the mapper side without any issue, but some data cause this failure
in the reducer side.
Thanks for your help.
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