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https://issues.apache.org/jira/browse/HADOOP-13619?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Steve Yang updated HADOOP-13619:
--------------------------------
    Description: 
library used: org.apache.hadoop:hadoop-openstack:2.6.0
We are loading avro files from Oracle Storage Service server (i.e., Swift 
server) into Spark DataFrame object through the Spark Data Source API. For 
example:
return hiveCtx.read().format("com.databricks.spark.avro").load(objectName);

The number of records is less than the actual record count in the avro file 
when reading the avro file from Storage Service server using OpenStack Swift 
API.

If we run a SQL on top of the returned data frome like "select count(\*) as C1 
from <temp table>" we can see the record count is smaller when reading the same 
avro file from local file system.

For a large avro file (awclassic.avro, 105M) the count is always wrong (42451 
records vs. 60855). From the log file we can see the reading os the file is 
splitted into 4:
2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/awclassic.avro:100663296+10044747
2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/awclassic.avro:33554432+33554432
2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/awclassic.avro:0+33554432
2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/awclassic.avro:67108864+33554432

For a smaller avro file (wine.avro, 19M) the count sometimes is correct (57076 
records) and sometimes wrong (26999 records). Run the same spark SQL 10 times 
back-to-back produces the following record count results:
run 1: 26999
run 2: 26999
run 3: 57076
run 4: 57056
run 5: 57076
run 6: 26999
run 7: 57076
run 8: 57076
run 9: 57076
run 10: 57076

For this wine.avro test case there are two splits:
2016-08-31 17:42:32 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/wine.avro:9965269+9965270
2016-08-31 17:42:32 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/wine.avro:0+9965269

I will attach a zip file containing the two avro files in question and the 
debugged log file section of reading wine.avro file - one with successful 
reading(C4.ok) and one with missing record reading(C5.miss).

  was:
library used: org.apache.hadoop:hadoop-openstack:2.6.0
We are loading avro files from Oracle Storage Service server (i.e., Swift 
server) into Spark DataFrame object through the Spark Data Source API. For 
example:
return hiveCtx.read().format("com.databricks.spark.avro").load(objectName);

The number of records is less than the actual record count in the avro file 
when reading the avro file from Storage Service server using OpenStack Swift 
API.

If we run a SQL on top of the returned data frome like "select count(*) as C1 
from <temp table>" we can see the record count is smaller when reading the same 
avro file from local file system.

For a large avro file (awclassic.avro, 105M) the count is always wrong (42451 
records vs. 60855). From the log file we can see the reading os the file is 
splitted into 4:
2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/awclassic.avro:100663296+10044747
2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/awclassic.avro:33554432+33554432
2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/awclassic.avro:0+33554432
2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/awclassic.avro:67108864+33554432

For a smaller avro file (wine.avro, 19M) the count sometimes is correct (57076 
records) and sometimes wrong (26999 records). Run the same spark SQL 10 times 
back-to-back produces the following record count results:
run 1: 26999
run 2: 26999
run 3: 57076
run 4: 57056
run 5: 57076
run 6: 26999
run 7: 57076
run 8: 57076
run 9: 57076
run 10: 57076

For this wine.avro test case there are two splits:
2016-08-31 17:42:32 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/wine.avro:9965269+9965270
2016-08-31 17:42:32 INFO HadoopRDD:59 - Input split: 
swift://qaTestData.oracleswift/testAvro/wine.avro:0+9965269

I will attach a zip file containing the two avro files in question and the 
debugged log file section of reading wine.avro file - one with successful 
reading(C4.ok) and one with missing record reading(C5.miss).


> missing data intermittently when reading avro file
> --------------------------------------------------
>
>                 Key: HADOOP-13619
>                 URL: https://issues.apache.org/jira/browse/HADOOP-13619
>             Project: Hadoop Common
>          Issue Type: Bug
>          Components: fs/swift
>    Affects Versions: 2.6.0
>         Environment: Linux EL6
>            Reporter: Steve Yang
>            Priority: Blocker
>
> library used: org.apache.hadoop:hadoop-openstack:2.6.0
> We are loading avro files from Oracle Storage Service server (i.e., Swift 
> server) into Spark DataFrame object through the Spark Data Source API. For 
> example:
> return hiveCtx.read().format("com.databricks.spark.avro").load(objectName);
> The number of records is less than the actual record count in the avro file 
> when reading the avro file from Storage Service server using OpenStack Swift 
> API.
> If we run a SQL on top of the returned data frome like "select count(\*) as 
> C1 from <temp table>" we can see the record count is smaller when reading the 
> same avro file from local file system.
> For a large avro file (awclassic.avro, 105M) the count is always wrong (42451 
> records vs. 60855). From the log file we can see the reading os the file is 
> splitted into 4:
> 2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
> swift://qaTestData.oracleswift/testAvro/awclassic.avro:100663296+10044747
> 2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
> swift://qaTestData.oracleswift/testAvro/awclassic.avro:33554432+33554432
> 2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
> swift://qaTestData.oracleswift/testAvro/awclassic.avro:0+33554432
> 2016-09-01 14:18:27 INFO HadoopRDD:59 - Input split: 
> swift://qaTestData.oracleswift/testAvro/awclassic.avro:67108864+33554432
> For a smaller avro file (wine.avro, 19M) the count sometimes is correct 
> (57076 records) and sometimes wrong (26999 records). Run the same spark SQL 
> 10 times back-to-back produces the following record count results:
> run 1: 26999
> run 2: 26999
> run 3: 57076
> run 4: 57056
> run 5: 57076
> run 6: 26999
> run 7: 57076
> run 8: 57076
> run 9: 57076
> run 10: 57076
> For this wine.avro test case there are two splits:
> 2016-08-31 17:42:32 INFO HadoopRDD:59 - Input split: 
> swift://qaTestData.oracleswift/testAvro/wine.avro:9965269+9965270
> 2016-08-31 17:42:32 INFO HadoopRDD:59 - Input split: 
> swift://qaTestData.oracleswift/testAvro/wine.avro:0+9965269
> I will attach a zip file containing the two avro files in question and the 
> debugged log file section of reading wine.avro file - one with successful 
> reading(C4.ok) and one with missing record reading(C5.miss).



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