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https://issues.apache.org/jira/browse/SPARK-8406?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14589592#comment-14589592
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Cheng Lian commented on SPARK-8406:
-----------------------------------
An example task completion and scheduling order that causes overwriting:
# Writing a DataFrame with 4 RDD partitions to an empty directory.
# Task 1 and task 2 get scheduled, while task 3 and task 4 are queued. Both
task 1 and task 2 find current max part number to be 0 (because destination
directory is empty).
# Task 1 finishes, generates {{part-r-00001.gz.parquet}}. Current max part
number becomes 1.
# Task 4 gets scheduled, decides to write to {{part-r-00005.gz.parquet}} (5 =
current max part number + task ID), but hasn't start writing the file yet.
# Task 2 finishes, generates {{part-r-00002.gz.parquet}}. Current max part
number becomes 2.
# Task 3 gets scheduled, also decides to write to {{part-r-00005.gz.parquet}}
since task 4 hasn't start writing its output file, and task 3 finds current max
part number is still 2.
# Task 4 finishes writing {{part-r-00005.gz.parquet}}
# Task 3 finishes writing {{part-r-00005.gz.parquet}}
# Output of task 4 is overwritten.
> Race condition when writing Parquet files
> -----------------------------------------
>
> Key: SPARK-8406
> URL: https://issues.apache.org/jira/browse/SPARK-8406
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.0
> Reporter: Cheng Lian
> Assignee: Cheng Lian
> Priority: Blocker
>
> To support appending, the Parquet data source tries to find out the max ID of
> part-files in the destination directory (the <id> in output file name
> "part-r-<id>.gz.parquet") at the beginning of the write job. In 1.3.0, this
> step happens on driver side before any files are written. However, in 1.4.0,
> this is moved to task side. Thus, for tasks scheduled later, they may see
> wrong max ID generated by newly written files by other finished tasks within
> the same job. This actually causes a race condition. In most cases, this only
> causes nonconsecutive IDs in output file names. But when the DataFrame
> contains thousands of RDD partitions, it's likely that two tasks may choose
> the same ID, thus one of them gets overwritten by the other.
> The data loss situation is not quite easy to reproduce. But the following
> Spark shell snippet can reproduce nonconsecutive output file IDs:
> {code}
> sqlContext.range(0,
> 128).repartition(16).write.mode("overwrite").parquet("foo")
> {code}
> "16" can be replaced with any integer that is greater than the default
> parallelism on your machine (usually it means core number, on my machine it's
> 8).
> {noformat}
> -rw-r--r-- 3 lian supergroup 0 2015-06-17 00:06
> /user/lian/foo/_SUCCESS
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00001.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00002.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00003.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00004.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00005.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00006.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00007.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00008.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00017.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00018.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00019.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00020.gz.parquet
> -rw-r--r-- 3 lian supergroup 352 2015-06-17 00:06
> /user/lian/foo/part-r-00021.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00022.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00023.gz.parquet
> -rw-r--r-- 3 lian supergroup 353 2015-06-17 00:06
> /user/lian/foo/part-r-00024.gz.parquet
> {noformat}
> Notice that the newly added ORC data source doesn't suffer this issue because
> it uses both task ID and {{System.currentTimeMills()}} to generate the output
> file name.
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