Re: [DISCUSS][SQL] Control the number of output files
we have found that to make shuffles reliable without OOMs we need to have spark.sql.shuffle.partitions at a high number, bigger than 2000 at least. yet this leads to a large amount of part files, which puts big pressure on spark driver programs. i tried to mitigate this with dataframe.coalesce to reduce the number of files, but this is not acceptable. coalesce changes the tasks for the last shuffle before it, bringing back the issues we tried to mitigate with a high number for spark.sql.shuffle.partitions in the first place. doing a dataframe.repartition before every write is also not an unacceptable approach, it is too high a price to pay just to bring down the number of files. so i am very excited about any approach that efficiently merges files when writing. On Mon, Aug 6, 2018 at 5:28 PM, lukas nalezenec wrote: > Hi Koert, > There is no such Jira yet. We need SPARK-23889 before. You can find some > mentions in the design document inside 23889. > Best regards > Lukas > > 2018-08-06 18:34 GMT+02:00 Koert Kuipers : > >> i went through the jiras targeting 2.4.0 trying to find a feature where >> spark would coalesce/repartition by size (so merge small files >> automatically), but didn't find it. >> can someone point me to it? >> thank you. >> best, >> koert >> >> On Sun, Aug 5, 2018 at 9:06 PM, Koert Kuipers wrote: >> >>> lukas, >>> what is the jira ticket for this? i would like to follow it's activity. >>> thanks! >>> koert >>> >>> On Wed, Jul 25, 2018 at 5:32 PM, lukas nalezenec >>> wrote: >>> Hi, Yes, This feature is planned - Spark should be soon able to repartition output by size. Lukas Dne st 25. 7. 2018 23:26 uživatel Forest Fang napsal: > Has there been any discussion to simply support Hive's merge small > files configuration? It simply adds one additional stage to inspect size > of > each output file, recompute the desired parallelism to reach a target > size, > and runs a map-only coalesce before committing the final files. Since > AFAIK > SparkSQL already stages the final output commit, it seems feasible to > respect this Hive config. > > https://community.hortonworks.com/questions/106987/hive-mult > iple-small-files.html > > > On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra > wrote: > >> See some of the related discussion under https://github.com/apach >> e/spark/pull/21589 >> >> If feels to me like we need some kind of user code mechanism to >> signal policy preferences to Spark. This could also include ways to >> signal >> scheduling policy, which could include things like scheduling pool and/or >> barrier scheduling. Some of those scheduling policies operate at >> inherently >> different levels currently -- e.g. scheduling pools at the Job level >> (really, the thread local level in the current implementation) and >> barrier >> scheduling at the Stage level -- so it is not completely obvious how to >> unify all of these policy options/preferences/mechanism, or whether it is >> possible, but I think it is worth considering such things at a fairly >> high >> level of abstraction and try to unify and simplify before making things >> more complex with multiple policy mechanisms. >> >> On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin >> wrote: >> >>> Seems like a good idea in general. Do other systems have similar >>> concepts? In general it'd be easier if we can follow existing >>> convention if >>> there is any. >>> >>> >>> On Wed, Jul 25, 2018 at 11:50 AM John Zhuge >>> wrote: >>> Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function *repartition*(n) or *coalesce*(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ *COALESCE*(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge >>> >>> >> >
Re: [DISCUSS][SQL] Control the number of output files
Hi Koert, There is no such Jira yet. We need SPARK-23889 before. You can find some mentions in the design document inside 23889. Best regards Lukas 2018-08-06 18:34 GMT+02:00 Koert Kuipers : > i went through the jiras targeting 2.4.0 trying to find a feature where > spark would coalesce/repartition by size (so merge small files > automatically), but didn't find it. > can someone point me to it? > thank you. > best, > koert > > On Sun, Aug 5, 2018 at 9:06 PM, Koert Kuipers wrote: > >> lukas, >> what is the jira ticket for this? i would like to follow it's activity. >> thanks! >> koert >> >> On Wed, Jul 25, 2018 at 5:32 PM, lukas nalezenec >> wrote: >> >>> Hi, >>> Yes, This feature is planned - Spark should be soon able to repartition >>> output by size. >>> Lukas >>> >>> >>> Dne st 25. 7. 2018 23:26 uživatel Forest Fang >>> napsal: >>> Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-mult iple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra wrote: > See some of the related discussion under https://github.com/apach > e/spark/pull/21589 > > If feels to me like we need some kind of user code mechanism to signal > policy preferences to Spark. This could also include ways to signal > scheduling policy, which could include things like scheduling pool and/or > barrier scheduling. Some of those scheduling policies operate at > inherently > different levels currently -- e.g. scheduling pools at the Job level > (really, the thread local level in the current implementation) and barrier > scheduling at the Stage level -- so it is not completely obvious how to > unify all of these policy options/preferences/mechanism, or whether it is > possible, but I think it is worth considering such things at a fairly high > level of abstraction and try to unify and simplify before making things > more complex with multiple policy mechanisms. > > On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin > wrote: > >> Seems like a good idea in general. Do other systems have similar >> concepts? In general it'd be easier if we can follow existing convention >> if >> there is any. >> >> >> On Wed, Jul 25, 2018 at 11:50 AM John Zhuge >> wrote: >> >>> Hi all, >>> >>> Many Spark users in my company are asking for a way to control the >>> number of output files in Spark SQL. There are use cases to either >>> reduce >>> or increase the number. The users prefer not to use function >>> *repartition*(n) or *coalesce*(n, shuffle) that require them to >>> write and deploy Scala/Java/Python code. >>> >>> Could we introduce a query hint for this purpose (similar to >>> Broadcast Join Hints)? >>> >>> /*+ *COALESCE*(n, shuffle) */ >>> >>> In general, is query hint is the best way to bring DF functionality >>> to SQL without extending SQL syntax? Any suggestion is highly >>> appreciated. >>> >>> This requirement is not the same as SPARK-6221 that asked for >>> auto-merging output files. >>> >>> Thanks, >>> John Zhuge >>> >> >> >
Re: [DISCUSS][SQL] Control the number of output files
i went through the jiras targeting 2.4.0 trying to find a feature where spark would coalesce/repartition by size (so merge small files automatically), but didn't find it. can someone point me to it? thank you. best, koert On Sun, Aug 5, 2018 at 9:06 PM, Koert Kuipers wrote: > lukas, > what is the jira ticket for this? i would like to follow it's activity. > thanks! > koert > > On Wed, Jul 25, 2018 at 5:32 PM, lukas nalezenec wrote: > >> Hi, >> Yes, This feature is planned - Spark should be soon able to repartition >> output by size. >> Lukas >> >> >> Dne st 25. 7. 2018 23:26 uživatel Forest Fang >> napsal: >> >>> Has there been any discussion to simply support Hive's merge small files >>> configuration? It simply adds one additional stage to inspect size of each >>> output file, recompute the desired parallelism to reach a target size, and >>> runs a map-only coalesce before committing the final files. Since AFAIK >>> SparkSQL already stages the final output commit, it seems feasible to >>> respect this Hive config. >>> >>> https://community.hortonworks.com/questions/106987/hive-mult >>> iple-small-files.html >>> >>> >>> On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra >>> wrote: >>> See some of the related discussion under https://github.com/apach e/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin wrote: > Seems like a good idea in general. Do other systems have similar > concepts? In general it'd be easier if we can follow existing convention > if > there is any. > > > On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: > >> Hi all, >> >> Many Spark users in my company are asking for a way to control the >> number of output files in Spark SQL. There are use cases to either reduce >> or increase the number. The users prefer not to use function >> *repartition*(n) or *coalesce*(n, shuffle) that require them to >> write and deploy Scala/Java/Python code. >> >> Could we introduce a query hint for this purpose (similar to >> Broadcast Join Hints)? >> >> /*+ *COALESCE*(n, shuffle) */ >> >> In general, is query hint is the best way to bring DF functionality >> to SQL without extending SQL syntax? Any suggestion is highly >> appreciated. >> >> This requirement is not the same as SPARK-6221 that asked for >> auto-merging output files. >> >> Thanks, >> John Zhuge >> > >
Re: [DISCUSS][SQL] Control the number of output files
Great help from the community! On Sun, Aug 5, 2018 at 6:17 PM Xiao Li wrote: > FYI, the new hints have been merged. They will be available in the > upcoming release (Spark 2.4). > > *John Zhuge*, thanks for your work! Really appreciate it! Please submit > more PRs and help the community improve Spark. : ) > > Xiao > > 2018-08-05 21:06 GMT-04:00 Koert Kuipers : > >> lukas, >> what is the jira ticket for this? i would like to follow it's activity. >> thanks! >> koert >> >> On Wed, Jul 25, 2018 at 5:32 PM, lukas nalezenec >> wrote: >> >>> Hi, >>> Yes, This feature is planned - Spark should be soon able to repartition >>> output by size. >>> Lukas >>> >>> >>> Dne st 25. 7. 2018 23:26 uživatel Forest Fang >>> napsal: >>> Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra wrote: > See some of the related discussion under > https://github.com/apache/spark/pull/21589 > > If feels to me like we need some kind of user code mechanism to signal > policy preferences to Spark. This could also include ways to signal > scheduling policy, which could include things like scheduling pool and/or > barrier scheduling. Some of those scheduling policies operate at > inherently > different levels currently -- e.g. scheduling pools at the Job level > (really, the thread local level in the current implementation) and barrier > scheduling at the Stage level -- so it is not completely obvious how to > unify all of these policy options/preferences/mechanism, or whether it is > possible, but I think it is worth considering such things at a fairly high > level of abstraction and try to unify and simplify before making things > more complex with multiple policy mechanisms. > > On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin > wrote: > >> Seems like a good idea in general. Do other systems have similar >> concepts? In general it'd be easier if we can follow existing convention >> if >> there is any. >> >> >> On Wed, Jul 25, 2018 at 11:50 AM John Zhuge >> wrote: >> >>> Hi all, >>> >>> Many Spark users in my company are asking for a way to control the >>> number of output files in Spark SQL. There are use cases to either >>> reduce >>> or increase the number. The users prefer not to use function >>> *repartition*(n) or *coalesce*(n, shuffle) that require them to >>> write and deploy Scala/Java/Python code. >>> >>> Could we introduce a query hint for this purpose (similar to >>> Broadcast Join Hints)? >>> >>> /*+ *COALESCE*(n, shuffle) */ >>> >>> In general, is query hint is the best way to bring DF functionality >>> to SQL without extending SQL syntax? Any suggestion is highly >>> appreciated. >>> >>> This requirement is not the same as SPARK-6221 that asked for >>> auto-merging output files. >>> >>> Thanks, >>> John Zhuge >>> >> >> > -- John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
https://issues.apache.org/jira/browse/SPARK-24940 The PR has been merged to 2.4.0. On Sun, Aug 5, 2018 at 6:06 PM Koert Kuipers wrote: > lukas, > what is the jira ticket for this? i would like to follow it's activity. > thanks! > koert > > On Wed, Jul 25, 2018 at 5:32 PM, lukas nalezenec wrote: > >> Hi, >> Yes, This feature is planned - Spark should be soon able to repartition >> output by size. >> Lukas >> >> >> Dne st 25. 7. 2018 23:26 uživatel Forest Fang >> napsal: >> >>> Has there been any discussion to simply support Hive's merge small files >>> configuration? It simply adds one additional stage to inspect size of each >>> output file, recompute the desired parallelism to reach a target size, and >>> runs a map-only coalesce before committing the final files. Since AFAIK >>> SparkSQL already stages the final output commit, it seems feasible to >>> respect this Hive config. >>> >>> >>> https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html >>> >>> >>> On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra >>> wrote: >>> See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin wrote: > Seems like a good idea in general. Do other systems have similar > concepts? In general it'd be easier if we can follow existing convention > if > there is any. > > > On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: > >> Hi all, >> >> Many Spark users in my company are asking for a way to control the >> number of output files in Spark SQL. There are use cases to either reduce >> or increase the number. The users prefer not to use function >> *repartition*(n) or *coalesce*(n, shuffle) that require them to >> write and deploy Scala/Java/Python code. >> >> Could we introduce a query hint for this purpose (similar to >> Broadcast Join Hints)? >> >> /*+ *COALESCE*(n, shuffle) */ >> >> In general, is query hint is the best way to bring DF functionality >> to SQL without extending SQL syntax? Any suggestion is highly >> appreciated. >> >> This requirement is not the same as SPARK-6221 that asked for >> auto-merging output files. >> >> Thanks, >> John Zhuge >> > > -- John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
FYI, the new hints have been merged. They will be available in the upcoming release (Spark 2.4). *John Zhuge*, thanks for your work! Really appreciate it! Please submit more PRs and help the community improve Spark. : ) Xiao 2018-08-05 21:06 GMT-04:00 Koert Kuipers : > lukas, > what is the jira ticket for this? i would like to follow it's activity. > thanks! > koert > > On Wed, Jul 25, 2018 at 5:32 PM, lukas nalezenec wrote: > >> Hi, >> Yes, This feature is planned - Spark should be soon able to repartition >> output by size. >> Lukas >> >> >> Dne st 25. 7. 2018 23:26 uživatel Forest Fang >> napsal: >> >>> Has there been any discussion to simply support Hive's merge small files >>> configuration? It simply adds one additional stage to inspect size of each >>> output file, recompute the desired parallelism to reach a target size, and >>> runs a map-only coalesce before committing the final files. Since AFAIK >>> SparkSQL already stages the final output commit, it seems feasible to >>> respect this Hive config. >>> >>> https://community.hortonworks.com/questions/106987/hive-mult >>> iple-small-files.html >>> >>> >>> On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra >>> wrote: >>> See some of the related discussion under https://github.com/apach e/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin wrote: > Seems like a good idea in general. Do other systems have similar > concepts? In general it'd be easier if we can follow existing convention > if > there is any. > > > On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: > >> Hi all, >> >> Many Spark users in my company are asking for a way to control the >> number of output files in Spark SQL. There are use cases to either reduce >> or increase the number. The users prefer not to use function >> *repartition*(n) or *coalesce*(n, shuffle) that require them to >> write and deploy Scala/Java/Python code. >> >> Could we introduce a query hint for this purpose (similar to >> Broadcast Join Hints)? >> >> /*+ *COALESCE*(n, shuffle) */ >> >> In general, is query hint is the best way to bring DF functionality >> to SQL without extending SQL syntax? Any suggestion is highly >> appreciated. >> >> This requirement is not the same as SPARK-6221 that asked for >> auto-merging output files. >> >> Thanks, >> John Zhuge >> > >
Re: [DISCUSS][SQL] Control the number of output files
lukas, what is the jira ticket for this? i would like to follow it's activity. thanks! koert On Wed, Jul 25, 2018 at 5:32 PM, lukas nalezenec wrote: > Hi, > Yes, This feature is planned - Spark should be soon able to repartition > output by size. > Lukas > > > Dne st 25. 7. 2018 23:26 uživatel Forest Fang > napsal: > >> Has there been any discussion to simply support Hive's merge small files >> configuration? It simply adds one additional stage to inspect size of each >> output file, recompute the desired parallelism to reach a target size, and >> runs a map-only coalesce before committing the final files. Since AFAIK >> SparkSQL already stages the final output commit, it seems feasible to >> respect this Hive config. >> >> https://community.hortonworks.com/questions/106987/hive- >> multiple-small-files.html >> >> >> On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra >> wrote: >> >>> See some of the related discussion under https://github.com/ >>> apache/spark/pull/21589 >>> >>> If feels to me like we need some kind of user code mechanism to signal >>> policy preferences to Spark. This could also include ways to signal >>> scheduling policy, which could include things like scheduling pool and/or >>> barrier scheduling. Some of those scheduling policies operate at inherently >>> different levels currently -- e.g. scheduling pools at the Job level >>> (really, the thread local level in the current implementation) and barrier >>> scheduling at the Stage level -- so it is not completely obvious how to >>> unify all of these policy options/preferences/mechanism, or whether it is >>> possible, but I think it is worth considering such things at a fairly high >>> level of abstraction and try to unify and simplify before making things >>> more complex with multiple policy mechanisms. >>> >>> On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin wrote: >>> Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: > Hi all, > > Many Spark users in my company are asking for a way to control the > number of output files in Spark SQL. There are use cases to either reduce > or increase the number. The users prefer not to use function > *repartition*(n) or *coalesce*(n, shuffle) that require them to write > and deploy Scala/Java/Python code. > > Could we introduce a query hint for this purpose (similar to Broadcast > Join Hints)? > > /*+ *COALESCE*(n, shuffle) */ > > In general, is query hint is the best way to bring DF functionality to > SQL without extending SQL syntax? Any suggestion is highly appreciated. > > This requirement is not the same as SPARK-6221 that asked for > auto-merging output files. > > Thanks, > John Zhuge >
Re: [DISCUSS][SQL] Control the number of output files
Filed https://issues.apache.org/jira/browse/SPARK-24940. Will upload a patch shortly. SPARK-20857 introduced a generic SQL Hint Framework since 2.2.0. On Thu, Jul 26, 2018 at 4:25 PM Reynold Xin wrote: > John, > > You want to create a ticket and submit a patch for this? If there is a > coalesce hint, inject a coalesce logical node. Pretty simple. > > > On Wed, Jul 25, 2018 at 2:48 PM John Zhuge wrote: > >> Thanks for the comment, Forest. What I am asking is to make whatever DF >> repartition/coalesce functionalities available to SQL users. >> >> Agree with you on that reducing the final number of output files by file >> size is very nice to have. Lukas indicated this is planned. >> >> On Wed, Jul 25, 2018 at 2:31 PM Forest Fang >> wrote: >> >>> Sorry I see https://issues.apache.org/jira/browse/SPARK-6221 was >>> referenced in John's email. Can you elaborate how is your requirement >>> different? In my experience, it usually is driven by the need to decrease >>> the final output parallelism without compromising compute parallelism (i.e. >>> to prevent too many small files to be persisted on HDFS.) The requirement >>> in my experience is often pretty ballpark and does not require precise >>> number of partitions. Therefore setting the desired output size to say >>> 32-64mb usually gives a good enough result. I'm curious why 6221 was marked >>> as won't fix. >>> >>> On Wed, Jul 25, 2018 at 2:26 PM Forest Fang >>> wrote: >>> Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra wrote: > See some of the related discussion under > https://github.com/apache/spark/pull/21589 > > If feels to me like we need some kind of user code mechanism to signal > policy preferences to Spark. This could also include ways to signal > scheduling policy, which could include things like scheduling pool and/or > barrier scheduling. Some of those scheduling policies operate at > inherently > different levels currently -- e.g. scheduling pools at the Job level > (really, the thread local level in the current implementation) and barrier > scheduling at the Stage level -- so it is not completely obvious how to > unify all of these policy options/preferences/mechanism, or whether it is > possible, but I think it is worth considering such things at a fairly high > level of abstraction and try to unify and simplify before making things > more complex with multiple policy mechanisms. > > On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin > wrote: > >> Seems like a good idea in general. Do other systems have similar >> concepts? In general it'd be easier if we can follow existing convention >> if >> there is any. >> >> >> On Wed, Jul 25, 2018 at 11:50 AM John Zhuge >> wrote: >> >>> Hi all, >>> >>> Many Spark users in my company are asking for a way to control the >>> number of output files in Spark SQL. There are use cases to either >>> reduce >>> or increase the number. The users prefer not to use function >>> *repartition*(n) or *coalesce*(n, shuffle) that require them to >>> write and deploy Scala/Java/Python code. >>> >>> Could we introduce a query hint for this purpose (similar to >>> Broadcast Join Hints)? >>> >>> /*+ *COALESCE*(n, shuffle) */ >>> >>> In general, is query hint is the best way to bring DF functionality >>> to SQL without extending SQL syntax? Any suggestion is highly >>> appreciated. >>> >>> This requirement is not the same as SPARK-6221 that asked for >>> auto-merging output files. >>> >>> Thanks, >>> John Zhuge >>> >> >> >> -- >> John Zhuge >> > -- John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
John, You want to create a ticket and submit a patch for this? If there is a coalesce hint, inject a coalesce logical node. Pretty simple. On Wed, Jul 25, 2018 at 2:48 PM John Zhuge wrote: > Thanks for the comment, Forest. What I am asking is to make whatever DF > repartition/coalesce functionalities available to SQL users. > > Agree with you on that reducing the final number of output files by file > size is very nice to have. Lukas indicated this is planned. > > On Wed, Jul 25, 2018 at 2:31 PM Forest Fang > wrote: > >> Sorry I see https://issues.apache.org/jira/browse/SPARK-6221 was >> referenced in John's email. Can you elaborate how is your requirement >> different? In my experience, it usually is driven by the need to decrease >> the final output parallelism without compromising compute parallelism (i.e. >> to prevent too many small files to be persisted on HDFS.) The requirement >> in my experience is often pretty ballpark and does not require precise >> number of partitions. Therefore setting the desired output size to say >> 32-64mb usually gives a good enough result. I'm curious why 6221 was marked >> as won't fix. >> >> On Wed, Jul 25, 2018 at 2:26 PM Forest Fang >> wrote: >> >>> Has there been any discussion to simply support Hive's merge small files >>> configuration? It simply adds one additional stage to inspect size of each >>> output file, recompute the desired parallelism to reach a target size, and >>> runs a map-only coalesce before committing the final files. Since AFAIK >>> SparkSQL already stages the final output commit, it seems feasible to >>> respect this Hive config. >>> >>> >>> https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html >>> >>> >>> On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra >>> wrote: >>> See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin wrote: > Seems like a good idea in general. Do other systems have similar > concepts? In general it'd be easier if we can follow existing convention > if > there is any. > > > On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: > >> Hi all, >> >> Many Spark users in my company are asking for a way to control the >> number of output files in Spark SQL. There are use cases to either reduce >> or increase the number. The users prefer not to use function >> *repartition*(n) or *coalesce*(n, shuffle) that require them to >> write and deploy Scala/Java/Python code. >> >> Could we introduce a query hint for this purpose (similar to >> Broadcast Join Hints)? >> >> /*+ *COALESCE*(n, shuffle) */ >> >> In general, is query hint is the best way to bring DF functionality >> to SQL without extending SQL syntax? Any suggestion is highly >> appreciated. >> >> This requirement is not the same as SPARK-6221 that asked for >> auto-merging output files. >> >> Thanks, >> John Zhuge >> > > > -- > John Zhuge >
Re: [DISCUSS][SQL] Control the number of output files
Thanks for the comment, Forest. What I am asking is to make whatever DF repartition/coalesce functionalities available to SQL users. Agree with you on that reducing the final number of output files by file size is very nice to have. Lukas indicated this is planned. On Wed, Jul 25, 2018 at 2:31 PM Forest Fang wrote: > Sorry I see https://issues.apache.org/jira/browse/SPARK-6221 was > referenced in John's email. Can you elaborate how is your requirement > different? In my experience, it usually is driven by the need to decrease > the final output parallelism without compromising compute parallelism (i.e. > to prevent too many small files to be persisted on HDFS.) The requirement > in my experience is often pretty ballpark and does not require precise > number of partitions. Therefore setting the desired output size to say > 32-64mb usually gives a good enough result. I'm curious why 6221 was marked > as won't fix. > > On Wed, Jul 25, 2018 at 2:26 PM Forest Fang > wrote: > >> Has there been any discussion to simply support Hive's merge small files >> configuration? It simply adds one additional stage to inspect size of each >> output file, recompute the desired parallelism to reach a target size, and >> runs a map-only coalesce before committing the final files. Since AFAIK >> SparkSQL already stages the final output commit, it seems feasible to >> respect this Hive config. >> >> >> https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html >> >> >> On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra >> wrote: >> >>> See some of the related discussion under >>> https://github.com/apache/spark/pull/21589 >>> >>> If feels to me like we need some kind of user code mechanism to signal >>> policy preferences to Spark. This could also include ways to signal >>> scheduling policy, which could include things like scheduling pool and/or >>> barrier scheduling. Some of those scheduling policies operate at inherently >>> different levels currently -- e.g. scheduling pools at the Job level >>> (really, the thread local level in the current implementation) and barrier >>> scheduling at the Stage level -- so it is not completely obvious how to >>> unify all of these policy options/preferences/mechanism, or whether it is >>> possible, but I think it is worth considering such things at a fairly high >>> level of abstraction and try to unify and simplify before making things >>> more complex with multiple policy mechanisms. >>> >>> On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin wrote: >>> Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: > Hi all, > > Many Spark users in my company are asking for a way to control the > number of output files in Spark SQL. There are use cases to either reduce > or increase the number. The users prefer not to use function > *repartition*(n) or *coalesce*(n, shuffle) that require them to write > and deploy Scala/Java/Python code. > > Could we introduce a query hint for this purpose (similar to Broadcast > Join Hints)? > > /*+ *COALESCE*(n, shuffle) */ > > In general, is query hint is the best way to bring DF functionality to > SQL without extending SQL syntax? Any suggestion is highly appreciated. > > This requirement is not the same as SPARK-6221 that asked for > auto-merging output files. > > Thanks, > John Zhuge > -- John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
Sorry I see https://issues.apache.org/jira/browse/SPARK-6221 was referenced in John's email. Can you elaborate how is your requirement different? In my experience, it usually is driven by the need to decrease the final output parallelism without compromising compute parallelism (i.e. to prevent too many small files to be persisted on HDFS.) The requirement in my experience is often pretty ballpark and does not require precise number of partitions. Therefore setting the desired output size to say 32-64mb usually gives a good enough result. I'm curious why 6221 was marked as won't fix. On Wed, Jul 25, 2018 at 2:26 PM Forest Fang mailto:forest.f...@outlook.com>> wrote: Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra mailto:m...@clearstorydata.com>> wrote: See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin mailto:r...@databricks.com>> wrote: Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge mailto:jzh...@apache.org>> wrote: Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ COALESCE(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
Sorry I see https://issues.apache.org/jira/browse/SPARK-6221 was referenced in John's email. Can you elaborate how is your requirement different? In my experience, it usually is driven by the need to decrease the final output parallelism without compromising compute parallelism (i.e. to prevent too many small files to be persisted on HDFS.) The requirement in my experience is often pretty ballpark and does not require precise number of partitions. Therefore setting the desired output size to say 32-64mb usually gives a good enough result. I'm curious why 6221 was marked as won't fix. On Wed, Jul 25, 2018 at 2:26 PM Forest Fang mailto:forest.f...@outlook.com>> wrote: Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra mailto:m...@clearstorydata.com>> wrote: See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin mailto:r...@databricks.com>> wrote: Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge mailto:jzh...@apache.org>> wrote: Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ COALESCE(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra mailto:m...@clearstorydata.com>> wrote: See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin mailto:r...@databricks.com>> wrote: Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge mailto:jzh...@apache.org>> wrote: Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ COALESCE(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra mailto:m...@clearstorydata.com>> wrote: See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin mailto:r...@databricks.com>> wrote: Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge mailto:jzh...@apache.org>> wrote: Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ COALESCE(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
Hi, Yes, This feature is planned - Spark should be soon able to repartition output by size. Lukas Dne st 25. 7. 2018 23:26 uživatel Forest Fang napsal: > Has there been any discussion to simply support Hive's merge small files > configuration? It simply adds one additional stage to inspect size of each > output file, recompute the desired parallelism to reach a target size, and > runs a map-only coalesce before committing the final files. Since AFAIK > SparkSQL already stages the final output commit, it seems feasible to > respect this Hive config. > > > https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html > > > On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra > wrote: > >> See some of the related discussion under >> https://github.com/apache/spark/pull/21589 >> >> If feels to me like we need some kind of user code mechanism to signal >> policy preferences to Spark. This could also include ways to signal >> scheduling policy, which could include things like scheduling pool and/or >> barrier scheduling. Some of those scheduling policies operate at inherently >> different levels currently -- e.g. scheduling pools at the Job level >> (really, the thread local level in the current implementation) and barrier >> scheduling at the Stage level -- so it is not completely obvious how to >> unify all of these policy options/preferences/mechanism, or whether it is >> possible, but I think it is worth considering such things at a fairly high >> level of abstraction and try to unify and simplify before making things >> more complex with multiple policy mechanisms. >> >> On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin wrote: >> >>> Seems like a good idea in general. Do other systems have similar >>> concepts? In general it'd be easier if we can follow existing convention if >>> there is any. >>> >>> >>> On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: >>> Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function *repartition*(n) or *coalesce*(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ *COALESCE*(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge >>>
Re: [DISCUSS][SQL] Control the number of output files
Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra mailto:m...@clearstorydata.com>> wrote: See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin mailto:r...@databricks.com>> wrote: Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge mailto:jzh...@apache.org>> wrote: Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ COALESCE(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
Sorry I see https://issues.apache.org/jira/browse/SPARK-6221 was referenced in John's email. Can you elaborate how is your requirement different? In my experience, it usually is driven by the need to decrease the final output parallelism without compromising compute parallelism (i.e. to prevent too many small files to be persisted on HDFS.) The requirement in my experience is often pretty ballpark and does not require precise number of partitions. Therefore setting the desired output size to say 32-64mb usually gives a good enough result. I'm curious why 6221 was marked as won't fix. On Wed, Jul 25, 2018 at 2:26 PM Forest Fang mailto:forest.f...@outlook.com>> wrote: Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra mailto:m...@clearstorydata.com>> wrote: See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin mailto:r...@databricks.com>> wrote: Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge mailto:jzh...@apache.org>> wrote: Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ COALESCE(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
Sorry I see https://issues.apache.org/jira/browse/SPARK-6221 was referenced in John's email. Can you elaborate how is your requirement different? In my experience, it usually is driven by the need to decrease the final output parallelism without compromising compute parallelism (i.e. to prevent too many small files to be persisted on HDFS.) The requirement in my experience is often pretty ballpark and does not require precise number of partitions. Therefore setting the desired output size to say 32-64mb usually gives a good enough result. I'm curious why 6221 was marked as won't fix. On Wed, Jul 25, 2018 at 2:26 PM Forest Fang mailto:forest.f...@outlook.com>> wrote: Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra mailto:m...@clearstorydata.com>> wrote: See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin mailto:r...@databricks.com>> wrote: Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge mailto:jzh...@apache.org>> wrote: Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ COALESCE(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
Has there been any discussion to simply support Hive's merge small files configuration? It simply adds one additional stage to inspect size of each output file, recompute the desired parallelism to reach a target size, and runs a map-only coalesce before committing the final files. Since AFAIK SparkSQL already stages the final output commit, it seems feasible to respect this Hive config. https://community.hortonworks.com/questions/106987/hive-multiple-small-files.html On Wed, Jul 25, 2018 at 1:55 PM Mark Hamstra mailto:m...@clearstorydata.com>> wrote: See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin mailto:r...@databricks.com>> wrote: Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge mailto:jzh...@apache.org>> wrote: Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function repartition(n) or coalesce(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ COALESCE(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
Re: [DISCUSS][SQL] Control the number of output files
See some of the related discussion under https://github.com/apache/spark/pull/21589 If feels to me like we need some kind of user code mechanism to signal policy preferences to Spark. This could also include ways to signal scheduling policy, which could include things like scheduling pool and/or barrier scheduling. Some of those scheduling policies operate at inherently different levels currently -- e.g. scheduling pools at the Job level (really, the thread local level in the current implementation) and barrier scheduling at the Stage level -- so it is not completely obvious how to unify all of these policy options/preferences/mechanism, or whether it is possible, but I think it is worth considering such things at a fairly high level of abstraction and try to unify and simplify before making things more complex with multiple policy mechanisms. On Wed, Jul 25, 2018 at 1:37 PM Reynold Xin wrote: > Seems like a good idea in general. Do other systems have similar concepts? > In general it'd be easier if we can follow existing convention if there is > any. > > > On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: > >> Hi all, >> >> Many Spark users in my company are asking for a way to control the number >> of output files in Spark SQL. There are use cases to either reduce or >> increase the number. The users prefer not to use function *repartition*(n) >> or *coalesce*(n, shuffle) that require them to write and deploy >> Scala/Java/Python code. >> >> Could we introduce a query hint for this purpose (similar to Broadcast >> Join Hints)? >> >> /*+ *COALESCE*(n, shuffle) */ >> >> In general, is query hint is the best way to bring DF functionality to >> SQL without extending SQL syntax? Any suggestion is highly appreciated. >> >> This requirement is not the same as SPARK-6221 that asked for >> auto-merging output files. >> >> Thanks, >> John Zhuge >> >
Re: [DISCUSS][SQL] Control the number of output files
Seems like a good idea in general. Do other systems have similar concepts? In general it'd be easier if we can follow existing convention if there is any. On Wed, Jul 25, 2018 at 11:50 AM John Zhuge wrote: > Hi all, > > Many Spark users in my company are asking for a way to control the number > of output files in Spark SQL. There are use cases to either reduce or > increase the number. The users prefer not to use function *repartition*(n) > or *coalesce*(n, shuffle) that require them to write and deploy > Scala/Java/Python code. > > Could we introduce a query hint for this purpose (similar to Broadcast > Join Hints)? > > /*+ *COALESCE*(n, shuffle) */ > > In general, is query hint is the best way to bring DF functionality to SQL > without extending SQL syntax? Any suggestion is highly appreciated. > > This requirement is not the same as SPARK-6221 that asked for auto-merging > output files. > > Thanks, > John Zhuge >
[DISCUSS][SQL] Control the number of output files
Hi all, Many Spark users in my company are asking for a way to control the number of output files in Spark SQL. There are use cases to either reduce or increase the number. The users prefer not to use function *repartition*(n) or *coalesce*(n, shuffle) that require them to write and deploy Scala/Java/Python code. Could we introduce a query hint for this purpose (similar to Broadcast Join Hints)? /*+ *COALESCE*(n, shuffle) */ In general, is query hint is the best way to bring DF functionality to SQL without extending SQL syntax? Any suggestion is highly appreciated. This requirement is not the same as SPARK-6221 that asked for auto-merging output files. Thanks, John Zhuge
