[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16815763#comment-16815763 ] Victor Tso commented on SPARK-20144: This one was clearly decided against. I ended up writing my own file source strategy, but because we support multiple deployments I had to write a separate one for 2.2, 2.3 and 2.4. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16815755#comment-16815755 ] David Greenberg commented on SPARK-20144: - Hello, this issue is also a major one for me. Almost all of the data I work with is has a natural sort order, and I store it in CSV, parquet, and orc. Unfortunately, some of my datasets are very large, and so I waste a lot of compute time loading those datasets out of storage due to Spark throwing out serialization information at load & store time. I would really like to see a solution to this problem, as it's fairly expensive to our bottom line when using spark. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16697410#comment-16697410 ] Dongjoon Hyun commented on SPARK-20144: --- Sorry, [~darabos]. IMHO, the proposed way is not consistent with the existing Apache Spark design choice. Also, it's not robust enough to be a part of Apache Spark because it misleads the user without the guarantee on sort-ness always. Lastly, it causes performance degradation because it may try open many small files first. I think you had better add your patch into your Spark build if you have. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16697319#comment-16697319 ] Daniel Darabos commented on SPARK-20144: So where do we go from here? Should I try to find a reviewer? > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[
https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16650817#comment-16650817
]
Daniel Darabos commented on SPARK-20144:
Thanks, those are good questions.
# The global option is not great, but it's the simplest. The code is already
controlled by two global options. ({{spark.sql.files.maxPartitionBytes}} and
{{spark.sql.files.openCostInBytes}}.) Why not one more?
# I'm not sure what {{LOAD DATA INPATH}} does. (Sorry...) But sure, users can
put random-name files in the directory and mess stuff up. Best protection
against that is not putting random-name files in the directory. :D
# The whole problem is not Parquet-specific. It affects all file types. The
{{part-1}} naming comes from Hadoop's
[FileOutputFormat|https://github.com/apache/hadoop/blob/release-2.7.1/hadoop-mapreduce-project/hadoop-mapreduce-client/hadoop-mapreduce-client-core/src/main/java/org/apache/hadoop/mapreduce/lib/output/FileOutputFormat.java#L270].
It's been like this forever and will never change. (I'd say it's more than a
convention.)
> spark.read.parquet no long maintains ordering of the data
> -
>
> Key: SPARK-20144
> URL: https://issues.apache.org/jira/browse/SPARK-20144
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.2
>Reporter: Li Jin
>Priority: Major
>
> Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is
> when we read parquet files in 2.0.2, the ordering of rows in the resulting
> dataframe is not the same as the ordering of rows in the dataframe that the
> parquet file was reproduced with.
> This is because FileSourceStrategy.scala combines the parquet files into
> fewer partitions and also reordered them. This breaks our workflows because
> they assume the ordering of the data.
> Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec
> changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with
> 2.1.
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[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16650779#comment-16650779 ] Dongjoon Hyun commented on SPARK-20144: --- [~silvermast] and [~darabos]. 1. The proposed `spark.sql.files.allowReordering` is a global option for all data sources. 2. In parquet tables, can we prevent some users execute 'LOAD DATA INPATH' to that folder with a random-name file? 3. Is there any way for Hive/Spark/Parquet to keep that naming convention in that table always? > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[
https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16650722#comment-16650722
]
Daniel Darabos commented on SPARK-20144:
Yeah, I'm not too happy about the alphabetical ordering either. I thought I
could simply not sort, and get the "original" order. But at the point where I
made my change, the files are already in a jumbled order. Maybe it's the file
system listing order, which could be anything.
99% of the time I'm just reading back a single partitioned Parquet file. In
this case the alphabetical ordering is the right ordering. ({{part-1}},
{{part-2}}, ...) The rows of the resulting DataFrame will be in the same
order as originally. So I think this issue is satisfied by the change. (The
test also demonstrates this.)
The 1% case (for me) is when I'm reading back multiple Parquet files with a
glob in a single {{spark.read.parquet("dir-\{0,5,10}")}} call. In this case it
would be nice to respect the order given by the user ({{dir-0}}, {{dir-5}},
{{dir-10}}). My PR messes this up. ({{dir-0}}, {{dir-10}}, {{dir-5}}) But at
least the partitions within each Parquet file will be contiguous. That's still
an improvement.
> spark.read.parquet no long maintains ordering of the data
> -
>
> Key: SPARK-20144
> URL: https://issues.apache.org/jira/browse/SPARK-20144
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.2
>Reporter: Li Jin
>Priority: Major
>
> Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is
> when we read parquet files in 2.0.2, the ordering of rows in the resulting
> dataframe is not the same as the ordering of rows in the dataframe that the
> parquet file was reproduced with.
> This is because FileSourceStrategy.scala combines the parquet files into
> fewer partitions and also reordered them. This breaks our workflows because
> they assume the ordering of the data.
> Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec
> changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with
> 2.1.
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[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16650704#comment-16650704 ] Victor Tso commented on SPARK-20144: It should, because by convention the parquet files are 0-padded numerically ordered. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16650642#comment-16650642 ] Dongjoon Hyun commented on SPARK-20144: --- For me, I don't think that PR resolve this issue, `spark.read.parquet no long maintains ordering of the data`. This issue asked 'data ordering'. The alphabetical file path order doesn't guarantee the order of the data, does it? > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16650492#comment-16650492 ] Daniel Darabos commented on SPARK-20144: Thanks Victor! I've expanded the test with a case where reordering is allowed, and I've added some explanatory comments in the test. [~dongjoon], what do you think? Should I try to foster more discussion? Or what could be a next step? > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16650303#comment-16650303 ] Victor Tso commented on SPARK-20144: I looked at the PR and liked what I saw. I would only suggest the test be duplicated for true and/or the PR comment be added to the test code itself. We have a customer where the records do not have a declared ordering of values but the records' appearance order is significant. Turning on our feature flag to use Spark's parquet reader violates their expectation of ordering so we are unable to shepherd them to this feature flag. Any help along the lines of this Jira and PR would be appreciated. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[
https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16642401#comment-16642401
]
Daniel Darabos commented on SPARK-20144:
Sorry, I had an idea for a quick fix for this and sent a pull request without
discussing it first. Let me copy the rationale from the PR:
I'm adding {{spark.sql.files.allowReordering}}, defaulting to {{true}}. When
set to {{true}} the behavior is as before. When set to {{false}}, the input
files are read in alphabetical order. This means partitions are read in the
{{part-1}}, {{part-2}}, {{part-3}}... order, recovering the same
ordering as before.
While *SPARK-20144* has been closed as "Not A Problem", I think this is still a
valuable feature. Spark has been
[touted|https://databricks.com/blog/2016/11/14/setting-new-world-record-apache-spark.html]
as the best tool for sorting. It certainly can sort data. But without this
change, it can not read back sorted data on the DataFrame API.
My practical use case is that we allow users to run their SQL expressions
through our UI. We also allow them to ask for the results to be persisted to
Parquet files. We noticed that if they do an {{ORDER BY}}, the ordering is lost
if they also ask for persistence. For example they might want to rank data
points by a score, so they can later get the top 10 or top 10,000,000 entries
easily. With this change we could fulfill this use case.
The fix is small and safe. (25 lines including test and docs, only changes
behavior when new flag is set.) Is there a reason not to do this?
> spark.read.parquet no long maintains ordering of the data
> -
>
> Key: SPARK-20144
> URL: https://issues.apache.org/jira/browse/SPARK-20144
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.2
>Reporter: Li Jin
>Priority: Major
>
> Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is
> when we read parquet files in 2.0.2, the ordering of rows in the resulting
> dataframe is not the same as the ordering of rows in the dataframe that the
> parquet file was reproduced with.
> This is because FileSourceStrategy.scala combines the parquet files into
> fewer partitions and also reordered them. This breaks our workflows because
> they assume the ordering of the data.
> Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec
> changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with
> 2.1.
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[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16642038#comment-16642038 ] Apache Spark commented on SPARK-20144: -- User 'darabos' has created a pull request for this issue: https://github.com/apache/spark/pull/22673 > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16642036#comment-16642036 ] Apache Spark commented on SPARK-20144: -- User 'darabos' has created a pull request for this issue: https://github.com/apache/spark/pull/22673 > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16494852#comment-16494852 ] sam commented on SPARK-20144: - Regarding the original issue of sorting, I agree with [~srowen] in that it should be up to the user to explicitly ask for sorted data. This is because fundamentally Spark implements the Map Reduce programming paradigm which is defined in terms of multisets. [~icexelloss] Please read [http://theory.stanford.edu/~sergei/papers/soda10-mrc.pdf] Regarding my issue of Spark reducing the number of partitions without any ask from the user I've created a separate issue: https://issues.apache.org/jira/browse/SPARK-24425 > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16494810#comment-16494810 ] Unai Sarasola commented on SPARK-20144: --- But if you want to have exactly a copy from your data in HDFS for example, this would made impossible to Spark to maintain the copy of the files exactly in both cases. Is that right > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin >Priority: Major > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[
https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16203882#comment-16203882
]
sam commented on SPARK-20144:
-
I think this is a regression. We used to be able to easily control the number
of output files / tasks based on num files and coalesce. Now I have to use
`repartition` to get the desired num files / partitions which is unnecessarily
expensive.
I've tried playing with spark.sql.files.maxPartitionBytes and
spark.sql.files.openCostInBytes to see if I can force the conventional
behaviour.
{code}
val ss = SparkSession.builder().appName("uber-cp").master(conf.master())
.config("spark.sql.files.maxPartitionBytes", 1)
.config("spark.sql.files.openCostInBytes", Long.MaxValue)
{code}
This didn't work. Spark just squashes all my parquet files into less
partitions.
Suggest a simple `option` on DataFrameReader that can disable this (or enable
it, default behaviour should be same as 1.6).
> spark.read.parquet no long maintains ordering of the data
> -
>
> Key: SPARK-20144
> URL: https://issues.apache.org/jira/browse/SPARK-20144
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.2
>Reporter: Li Jin
>
> Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is
> when we read parquet files in 2.0.2, the ordering of rows in the resulting
> dataframe is not the same as the ordering of rows in the dataframe that the
> parquet file was reproduced with.
> This is because FileSourceStrategy.scala combines the parquet files into
> fewer partitions and also reordered them. This breaks our workflows because
> they assume the ordering of the data.
> Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec
> changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with
> 2.1.
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[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[
https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15996517#comment-15996517
]
Bill commented on SPARK-20144:
--
Increasing {{spark.sql.files.openCostInBytes}} prevents the individual parquet
files from being combined, but it does not prevent them from being reordered:
[DataSourceScanExec - spark
2.1.0|https://github.com/apache/spark/blob/v2.1.0/sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.scala#L499]
It seems somewhat inconsistent to respect the within-file ordering of a
file-based source (parquet in this case), but not the between-file ordering,
even though the order of files can also convey information.
Does it make sense to include an option that tells spark to also respect the
file order for a file-based source when constructing the partition list?
Multiple small files could still be combined into the same partition for
efficiency, but this would allow the user to tell spark that the order of files
matters and should be kept (within and between partitions).
> spark.read.parquet no long maintains ordering of the data
> -
>
> Key: SPARK-20144
> URL: https://issues.apache.org/jira/browse/SPARK-20144
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.2
>Reporter: Li Jin
>
> Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is
> when we read parquet files in 2.0.2, the ordering of rows in the resulting
> dataframe is not the same as the ordering of rows in the dataframe that the
> parquet file was reproduced with.
> This is because FileSourceStrategy.scala combines the parquet files into
> fewer partitions and also reordered them. This breaks our workflows because
> they assume the ordering of the data.
> Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec
> changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with
> 2.1.
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[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[
https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15961170#comment-15961170
]
Andrew Ash commented on SPARK-20144:
This is a regression from 1.6 to the 2.x line. [~marmbrus] recommended
modifying {{spark.sql.files.openCostInBytes}} as a workaround in this post:
http://apache-spark-developers-list.1001551.n3.nabble.com/Sorting-within-partitions-is-not-maintained-in-parquet-td18618.html#a18627
> spark.read.parquet no long maintains ordering of the data
> -
>
> Key: SPARK-20144
> URL: https://issues.apache.org/jira/browse/SPARK-20144
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.2
>Reporter: Li Jin
>
> Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is
> when we read parquet files in 2.0.2, the ordering of rows in the resulting
> dataframe is not the same as the ordering of rows in the dataframe that the
> parquet file was reproduced with.
> This is because FileSourceStrategy.scala combines the parquet files into
> fewer partitions and also reordered them. This breaks our workflows because
> they assume the ordering of the data.
> Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec
> changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with
> 2.1.
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[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15956030#comment-15956030 ] Li Jin commented on SPARK-20144: > When you save the sorted data into Parquet, only the data in individual > Parquet file can maintain the data ordering This is something changed in Spark 2 as well? write.parquet doesn't write parquet files in the order of partitions any more? > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15954559#comment-15954559 ] Liang-Chi Hsieh commented on SPARK-20144: - I don't think the API has the guarantee about the data ordering. The difference between 1.6.3 to 2.0.2 is just due to the change of internal implementation. I checked the current FileSourceScanExec, it still reorders the partition files. When you save the sorted data into Parquet, only the data in individual Parquet file can maintain the data ordering. We shouldn't expect a special ordering on the whole data read back, if the API doesn't explicitly guarantee that. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15951202#comment-15951202 ] Li Jin commented on SPARK-20144: Thanks Sean! I appreciate your time and help very much. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15951095#comment-15951095 ] Sean Owen commented on SPARK-20144: --- Probably best to wait for an informed opinion but I would assume for now you need to sort. I'm just saying that theoretically sorted data needs no data movement to become sorted because it is already. It may not actually even be expensive > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15951084#comment-15951084 ] Li Jin commented on SPARK-20144: Also, I am not sure about "If the data were sorted, sorting would be pretty cheap". Can you explain more on this? > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15951073#comment-15951073 ] Li Jin commented on SPARK-20144: I totally agree Correctness takes precedence. If sorting is the only way, we will do that, but I think there is way we can maintain ordering in parquet format. Parquet itself doesn't change the ordering, data in parquet is stored with parquet_file_0, parquet_file_1 ... and data are ordered within those files. However, it is FileSourceStrategy (https://github.com/apache/spark/blob/v2.0.2/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileSourceStrategy.scala#L168) that resorts parquet files and end up changing the ordering. If the expected semantics of Parquet doesn't maintain order, I won't complain the behavior of spark.read.parquet, but it seems it's Catalyst that is changing the ordering here. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15950988#comment-15950988 ] Sean Owen commented on SPARK-20144: --- If the data were sorted, sorting would be pretty cheap, in general. Correctness has to take precedence in any event, if you're describing this as a blocker for you. I don't believe projection can change ordering, no. I am saying that I would not necessarily expect that to extend to external serialization. I don't see that being tabular or on HDFS matters. I think some serializations would naturally preserve order and others would not. I am still not 100% sure what the expected semantics of Parquet are here, but you have de facto evidence it is not guaranteed. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[
https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15950979#comment-15950979
]
Li Jin commented on SPARK-20144:
Thanks for getting back to me.
Sorting in this case will just add extra cost to in our workflow and we are
trying to avoid it in the first place.
Because DataFrame presents the data in a tabular format, it is very surprising
that the table changes after going through hdfs. In any other tabular format
that I know of, ordering of rows is a property of the data and it is surprising
that reading/writing changes properties of the data. This is also a bit scary
because if ordering were not a property of a DataFrame, can things like cache
or select("col") change ordering of rows in the future?
> spark.read.parquet no long maintains ordering of the data
> -
>
> Key: SPARK-20144
> URL: https://issues.apache.org/jira/browse/SPARK-20144
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 2.0.2
>Reporter: Li Jin
>
> Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is
> when we read parquet files in 2.0.2, the ordering of rows in the resulting
> dataframe is not the same as the ordering of rows in the dataframe that the
> parquet file was reproduced with.
> This is because FileSourceStrategy.scala combines the parquet files into
> fewer partitions and also reordered them. This breaks our workflows because
> they assume the ordering of the data.
> Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec
> changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with
> 2.1.
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[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15950627#comment-15950627 ] Sean Owen commented on SPARK-20144: --- If you need a particular ordering, I think you need to sort. I am not sure ordering is particularly guaranteed in the format or the reading of it. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-20144) spark.read.parquet no long maintains ordering of the data
[ https://issues.apache.org/jira/browse/SPARK-20144?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15950221#comment-15950221 ] Li Jin commented on SPARK-20144: Ping, anyone? This is a pretty big blocker for us. > spark.read.parquet no long maintains ordering of the data > - > > Key: SPARK-20144 > URL: https://issues.apache.org/jira/browse/SPARK-20144 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.0.2 >Reporter: Li Jin > > Hi, We are trying to upgrade Spark from 1.6.3 to 2.0.2. One issue we found is > when we read parquet files in 2.0.2, the ordering of rows in the resulting > dataframe is not the same as the ordering of rows in the dataframe that the > parquet file was reproduced with. > This is because FileSourceStrategy.scala combines the parquet files into > fewer partitions and also reordered them. This breaks our workflows because > they assume the ordering of the data. > Is this considered a bug? Also FileSourceStrategy and FileSourceScanExec > changed quite a bit from 2.0.2 to 2.1, so not sure if this is an issue with > 2.1. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
