Images don't render on the mailing list. :( Seems like the issue if fixed now?
On Tue, May 7, 2019 at 10:15 PM Jun Zhu <[email protected]> wrote: > Hi, > I run the new code pull from master branch, and compare with another > stream job which run hudi 0.4.5 on maven. Both running per 10 minutes. > The roll-back worked. > Top is 0.4.5, bottom is 0.4.6 > [image: Screen Shot 2019-05-08 at 1.06.17 PM.png] > [image: Screen Shot 2019-05-08 at 1.06.54 PM.png] > And about log, I rewrite the log.trace to log.error to avoid log explode > with trace. > And There is nothing in variable: > >> 19/05/07 06:30:36 ERROR HoodieSparkSQLWriter: insert failed with 1 errors >> : >> 19/05/07 06:30:36 ERROR HoodieSparkSQLWriter: Printing out the top 100 >> errors >> ....spark log.... >> 19/05/07 06:30:36 ERROR HoodieSparkSQLWriter: Global error : >> .....spark log.... >> 19/05/07 07:10:40 ERROR HoodieSparkSQLWriter: insert failed with 1 errors >> : >> 19/05/07 07:10:40 ERROR HoodieSparkSQLWriter: Printing out the top 100 >> errors > > > Thanks, > Jun > > On Sat, May 4, 2019 at 11:31 AM Vinoth Chandar <[email protected]> wrote: > >> No worries. This just landed on master, you can give it a shot. You ll >> also >> end up picking up interval tree based filtering for global index, which >> will speed things along a lot. Fyi >> >> Have a good holiday! >> >> Thanks >> Vinoth >> >> On Fri, May 3, 2019 at 7:19 PM Jun Zhu <[email protected]> >> wrote: >> >> > Hi team, >> > i will try that, thank you so much, sorry for late reply, just have a >> > holiday in china😅. >> > Thanks >> > Jun >> > >> > On Wed, May 1, 2019 at 7:08 PM Vinoth Chandar <[email protected]> >> wrote: >> > >> > > Hi Jun, >> > > >> > > I was able to track that the HoodieSparkSQLWriter (common path for >> > > streaming sink and batch datasource) ends up calling >> > > DataSourceUtils.createHoodieClient, which creates the client as >> follows >> > > >> > > return new HoodieWriteClient<>(jssc, writeConfig); >> > > >> > > There is a third parameter that denotes whether the writer needs to >> > > rollback inflights. For e.g, DeltaStreamer invokes >> > > >> > > HoodieWriteClient client = new HoodieWriteClient<>(jssc, hoodieCfg, >> > true); >> > > >> > > While I trace down why we had this difference, could you try changing >> > this >> > > one line here, and add third "true" argument and give it a shot. >> > > >> > > >> > >> https://github.com/apache/incubator-hudi/blob/b34a204a527a156406908686e54484a0c3d8a3d7/hoodie-spark/src/main/java/com/uber/hoodie/DataSourceUtils.java#L148 >> > > >> > > >> > > Thanks >> > > Vinoth >> > > >> > > On Tue, Apr 30, 2019 at 11:16 PM [email protected] < >> [email protected]> >> > > wrote: >> > > >> > > > >> > > > Hi Jun, >> > > > You had mentioned that you are seeing the log message >> > > > "insert failed with 1 errors" >> > > > Did you see any exception stack traces before this message. You can >> > also >> > > > take a look at spark UI to see if stdout/stderr of failed tasks (if >> > > > present). >> > > > Also, it looks like if you also enable "trace" level logging, you >> would >> > > > see exceptions getting logged at the end. So, enabling "trace" level >> > > > logging is another way to debug what is happening. >> > > > '''log.error(s"$operation failed with ${errorCount} errors :"); >> > > > if (log.isTraceEnabled) { >> > > > log.trace("Printing out the top 100 errors") ....... >> > > > ''' >> > > > Balaji.V >> > > > >> > > > On Tuesday, April 30, 2019, 8:17:57 AM PDT, Vinoth Chandar < >> > > > [email protected]> wrote: >> > > > >> > > > Hi Jun, >> > > > >> > > > Basically you are saying streaming path leaves some inflights >> behind.. >> > > let >> > > > me see if I can reproduce it. If you have a simple test case, please >> > > share >> > > > >> > > > Thanks >> > > > Vinoth >> > > > >> > > > On Tue, Apr 30, 2019 at 1:04 AM Jun Zhu <[email protected] >> > >> > > > wrote: >> > > > >> > > > > Hi Vinoth, >> > > > > In spark streaming log I find "2019-04-30 03:26:11 ERROR >> > > > > HoodieSparkSQLWriter:182 - insert failed with 1 errors :"(no >> continue >> > > > error >> > > > > logs) , during which commit end with inflight and not cleaned. >> > > > > Just for feedback, we can dedup data correctly in batch way. >> Should >> > add >> > > > > more logic for exception handling if using spark stream I think. >> > > > > Regards, >> > > > > Jun >> > > > > >> > > > > >> > > > > On Tue, Apr 30, 2019 at 2:46 AM Vinoth Chandar <[email protected] >> > >> > > > wrote: >> > > > > >> > > > > > Another option to try would be setting the >> > > > > > spark.sql.hive.convertMetastoreParquet=false, if you are >> querying >> > via >> > > > the >> > > > > > Hive table registered by Hudi. >> > > > > > >> > > > > > On Sat, Apr 27, 2019 at 7:02 PM Jun Zhu >> <[email protected] >> > > >> > > > > > wrote: >> > > > > > >> > > > > > > Thanks for explanation vinoth, code was same list in >> > > > > > > https://github.com/apache/incubator-hudi/issues/639, with >> > setting >> > > > > table >> > > > > > > format to >> `.option(DataSourceWriteOptions.STORAGE_TYPE_OPT_KEY, >> > > > > > > DataSourceWriteOptions.MOR_STORAGE_TYPE_OPT_VAL)`. >> > > > > > > And the result data was stored on aws s3. >> > > > > > > I will try more on >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> `spark.sparkContext.hadoopConfiguration.setClass("mapreduce.input.pathFilter.class", >> > > > > > > classOf[com.uber.hoodie.hadoop.HoodieROTablePathFilter], >> > > > > > > classOf[org.apache.hadoop.fs.PathFilter]);` from the >> phenomenon, >> > > the >> > > > > > > config did not take effects maybe. >> > > > > > > >> > > > > > > On Sat, Apr 27, 2019 at 12:09 AM Vinoth Chandar < >> > [email protected] >> > > > >> > > > > > wrote: >> > > > > > > >> > > > > > > > Hi, >> > > > > > > > >> > > > > > > > >>The duplicates was found in inflight commit parquet files. >> > > > > Wondering >> > > > > > if >> > > > > > > > this was expected? >> > > > > > > > Spark shell should not even be reading in-flight parquet >> files. >> > > Can >> > > > > you >> > > > > > > > double check if the spark access is properly configured? >> > > > > > > > http://hudi.apache.org/querying_data.html#spark >> > > > > > > > >> > > > > > > > Inflight should be rolled back at the start of the next >> > > > commit/delta >> > > > > > > > commit.. Not sure why there are so many inflight delta >> commits. >> > > > > > > > If you can give a reproducible case, happy to debug it >> more.. >> > > > > > > > >> > > > > > > > Only complete instants are archived.. So yes, inflight is >> not >> > > > > > archived.. >> > > > > > > > >> > > > > > > > Hope that helps >> > > > > > > > >> > > > > > > > Thanks >> > > > > > > > Vinoth >> > > > > > > > >> > > > > > > > On Fri, Apr 26, 2019 at 2:09 AM Jun Zhu >> > > <[email protected] >> > > > > >> > > > > > > > wrote: >> > > > > > > > >> > > > > > > > > Hi Vinoth, >> > > > > > > > > Some continue question about this thread. >> > > > > > > > > Here is what I found after running a few days: >> > > > > > > > > in .hoodie folder, due to retain policy maybe, there is an >> > > > > obviously >> > > > > > > > > line(list in the end of email). Before it the cleaned >> commit >> > > was >> > > > > > > > archived, >> > > > > > > > > find duplication when query inflight commit correspond >> > > partition >> > > > by >> > > > > > > > > spark-shell. After the line, all behave normal, global >> dedup >> > > > works. >> > > > > > > > > The duplicates was found in inflight commit parquet files. >> > > > > Wondering >> > > > > > if >> > > > > > > > > this was expected? >> > > > > > > > > Q: >> > > > > > > > > 1. The inflight commit should be turned to roll back >> status >> > in >> > > > > next >> > > > > > > > > writes. Is it normal that so many inflight commit did not >> > make >> > > > it? >> > > > > Or >> > > > > > > > can I >> > > > > > > > > config a retain policy to turn inflight to roll_back in >> > another >> > > > > way? >> > > > > > > > > 2. Did commit retain policy do not archive inflight >> commit? >> > > > > > > > > >> > > > > > > > > 2019-04-23 20:23:47 378 >> > > > 20190423122339.deltacommit.inflight >> > > > > > > > > >> > > > > > > > > 2019-04-23 20:43:53 378 >> > > > 20190423124343.deltacommit.inflight >> > > > > > > > > >> > > > > > > > > 2019-04-23 22:14:04 378 >> > > > 20190423141354.deltacommit.inflight >> > > > > > > > > >> > > > > > > > > 2019-04-23 22:44:09 378 >> > > > 20190423144400.deltacommit.inflight >> > > > > > > > > >> > > > > > > > > 2019-04-23 22:54:18 378 >> > > > 20190423145408.deltacommit.inflight >> > > > > > > > > >> > > > > > > > > 2019-04-23 23:04:09 378 >> > > > 20190423150400.deltacommit.inflight >> > > > > > > > > >> > > > > > > > > 2019-04-23 23:24:30 378 >> > > > 20190423152421.deltacommit.inflight >> > > > > > > > > >> > > > > > > > > *2019-04-23 23:44:34 378 >> > > > > 20190423154424.deltacommit.inflight* >> > > > > > > > > >> > > > > > > > > *2019-04-24 00:15:46 2991 20190423161431.clean* >> > > > > > > > > >> > > > > > > > > 2019-04-24 00:15:21 870536 20190423161431.deltacommit >> > > > > > > > > >> > > > > > > > > 2019-04-24 00:25:19 2991 20190423162424.clean >> > > > > > > > > >> > > > > > > > > 2019-04-24 00:25:09 875825 20190423162424.deltacommit >> > > > > > > > > >> > > > > > > > > 2019-04-24 00:35:26 2991 20190423163429.clean >> > > > > > > > > >> > > > > > > > > 2019-04-24 00:35:18 881925 20190423163429.deltacommit >> > > > > > > > > >> > > > > > > > > 2019-04-24 00:46:14 2991 20190423164428.clean >> > > > > > > > > >> > > > > > > > > 2019-04-24 00:45:44 888025 20190423164428.deltacommit >> > > > > > > > > >> > > > > > > > > Thanks, >> > > > > > > > > Jun >> > > > > > > > > >> > > > > > > > > On 2019/04/18 14:29:23, Vinoth Chandar <[email protected]> >> > > wrote: >> > > > > > > > > > Hi Jun,> >> > > > > > > > > > >> > > > > > > > > > Responses below.> >> > > > > > > > > > >> > > > > > > > > > >>1. Some file inflight may never reach commit?> >> > > > > > > > > > yes. the next attempt at writing will first issue a >> > rollback >> > > to >> > > > > > clean >> > > > > > > > up> >> > > > > > > > > > such partial/leftover files first, before it begins the >> new >> > > > > > commit.> >> > > > > > > > > > >> > > > > > > > > > >>2. In occasion which inflight and parquet file >> generated >> > by >> > > > > > > inflight >> > > > > > > > > still> >> > > > > > > > > > exists, the global dedup will not dedup based on such >> kind >> > > > > file?> >> > > > > > > > > > even if not rolled back, we check for the inflight >> parquet >> > > > files >> > > > > > > > against> >> > > > > > > > > > the committed timeline, which it wont be a part of. So >> > should >> > > > be >> > > > > > > safe.> >> > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > > >>3. In occasion which inflight and parquet file >> generated >> > by >> > > > > > > inflight >> > > > > > > > > still> >> > > > > > > > > > exists, the correct query result will be decided by >> read >> > > > > config(I> >> > > > > > > > > > mean mapreduce.input.pathFilter.class> >> > > > > > > > > > in sparksql)> >> > > > > > > > > > yes. the filtering should work as well. its the same >> > > technique >> > > > > used >> > > > > > > by> >> > > > > > > > > > writer.> >> > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > > >>4. Is there any way we can use> >> > > > > > > > > > >> > > > > > > > > > >> >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> spark.sparkContext.hadoopConfiguration.setClass("mapreduce.input.pathFilter.class",> >> > > > > > > > > >> > > > > > > > > > > >> classOf[com.uber.hoodie.hadoop.HoodieROTablePathFilter],> >> > > > > > > > > > > classOf[org.apache.hadoop.fs.PathFilter]);> >> > > > > > > > > > >> > > > > > > > > > in spark thrift server when start it?> >> > > > > > > > > > >> > > > > > > > > > I am not familiar with the Spark thrift server myself. >> Any >> > > > > pointers >> > > > > > > > where >> > > > > > > > > I> >> > > > > > > > > > can learn more?> >> > > > > > > > > > Two suggestions :> >> > > > > > > > > > - You can check if you can add this to the Hadoop >> > > configuration >> > > > > xml >> > > > > > > > > files> >> > > > > > > > > > and see if it gets picked up by Spark?> >> > > > > > > > > > - Alternatively, you can set the spark config mentioned >> > here> >> > > > > > > > > > http://hudi.apache.org/querying_data.html#spark-rt-view >> > > (works >> > > > > for >> > > > > > > ro >> > > > > > > > > view> >> > > > > > > > > > also), which should be doable I am assuming at this >> thrift >> > > > > server> >> > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > > Thanks> >> > > > > > > > > > Vinoth> >> > > > > > > > > > >> > > > > > > > > > >> > > > > > > > > > On Wed, Apr 17, 2019 at 12:08 AM Jun Zhu >> > > > > <[email protected] >> > > > > > > >> > > > > > > > > wrote:> >> > > > > > > > > > >> > > > > > > > > > > Hi,> >> > > > > > > > > > > Link: >> > https://github.com/apache/incubator-hudi/issues/639> >> > > > > > > > > > > Sorry , failed open >> > > > > > > > > https://lists.apache.org/[email protected]> >> > > > > > > > > > > .> >> > > > > > > > > > > I have some follow up questions for issue 639:> >> > > > > > > > > > >> >> > > > > > > > > > > So, the sequence of events is . We write parquet files >> > and >> > > > then >> > > > > > > upon> >> > > > > > > > > > > > successful writing of all attempted parquet files, >> we >> > > > > actually >> > > > > > > make >> > > > > > > > > the> >> > > > > > > > > > > > commit as completed. (i.e not inflight anymore). So >> > this >> > > is >> > > > > > > normal. >> > > > > > > > > This> >> > > > > > > > > > > is> >> > > > > > > > > > > > done to prevent queries from reading partially >> written >> > > > > parquet >> > > > > > > > > files..> >> > > > > > > > > > > >> >> > > > > > > > > > >> >> > > > > > > > > > > Does that mean:> >> > > > > > > > > > > 1. Some file inflight may never reach commit?> >> > > > > > > > > > > 2. In occasion which inflight and parquet file >> generated >> > by >> > > > > > > inflight >> > > > > > > > > still> >> > > > > > > > > > > exists, the global dedup will not dedup based on such >> > kind >> > > > > > file?> >> > > > > > > > > > > 3. In occasion which inflight and parquet file >> generated >> > by >> > > > > > > inflight >> > > > > > > > > still> >> > > > > > > > > > > exists, the correct query result will be decided by >> read >> > > > > > config(I> >> > > > > > > > > > > mean mapreduce.input.pathFilter.class> >> > > > > > > > > > > in sparksql)> >> > > > > > > > > > > 4. Is there any way we can use> >> > > > > > > > > > >> >> > > > > > > > > > > >> >> > > > > > > > > > > >> > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> spark.sparkContext.hadoopConfiguration.setClass("mapreduce.input.pathFilter.class",> >> > > > > > > > > >> > > > > > > > > > > > >> > classOf[com.uber.hoodie.hadoop.HoodieROTablePathFilter],> >> > > > > > > > > > > > classOf[org.apache.hadoop.fs.PathFilter]);> >> > > > > > > > > > >> >> > > > > > > > > > > in spark thrift server when start it?> >> > > > > > > > > > >> >> > > > > > > > > > > Best,> >> > > > > > > > > > > --> >> > > > > > > > > > > [image: vshapesaqua11553186012.gif] < >> https://vungle.com/ >> > > >> > > > > *Jun >> > > > > > > > Zhu*> >> > > > > > > > > > > Sr. Engineer I, Data> >> > > > > > > > > > > ＋86 18565739171> >> > > > > > > > > > >> >> > > > > > > > > > > [image: in1552694272.png] < >> > > > > > https://www.linkedin.com/company/vungle >> > > > > > > >> >> > > > > > > > > > > [image:> >> > > > > > > > > > > fb1552694203.png] <https://facebook.com/vungle> >> > > > [image:> >> > > > > > > > > > > tw1552694330.png] <https://twitter.com/vungle> >> > > [image:> >> > > > > > > > > > > ig1552694392.png] <https://www.instagram.com/vungle>> >> > > > > > > > > > > Units 3801, 3804, 38F, C Block, Beijing Yintai Center, >> > > > Beijing, >> > > > > > > > China> >> > > > > > > > > > >> >> > > > > > > > > > >> > > > > > > > > >> > > > > > > > >> > > > > > > >> > > > > > > >> > > > > > > -- >> > > > > > > [image: vshapesaqua11553186012.gif] <https://vungle.com/> >> *Jun >> > > Zhu* >> > > > > > > Sr. Engineer I, Data >> > > > > > > ＋86 18565739171 >> > > > > > > >> > > > > > > [image: in1552694272.png] < >> > https://www.linkedin.com/company/vungle >> > > > >> > > > > > > [image: >> > > > > > > fb1552694203.png] <https://facebook.com/vungle> [image: >> > > > > > > tw1552694330.png] <https://twitter.com/vungle> [image: >> > > > > > > ig1552694392.png] <https://www.instagram.com/vungle> >> > > > > > > Units 3801, 3804, 38F, C Block, Beijing Yintai Center, >> Beijing, >> > > China >> > > > > > > >> > > > > > >> > > > > >> > > > > >> > > > > -- >> > > > > [image: vshapesaqua11553186012.gif] <https://vungle.com/> *Jun >> Zhu* >> > > > > Sr. Engineer I, Data >> > > > > ＋86 18565739171 >> > > > > >> > > > > [image: in1552694272.png] < >> https://www.linkedin.com/company/vungle> >> > > > > [image: >> > > > > fb1552694203.png] <https://facebook.com/vungle> [image: >> > > > > tw1552694330.png] <https://twitter.com/vungle> [image: >> > > > > ig1552694392.png] <https://www.instagram.com/vungle> >> > > > > Units 3801, 3804, 38F, C Block, Beijing Yintai Center, Beijing, >> China >> > > > > >> > > >> > >> > >> > -- >> > [image: vshapesaqua11553186012.gif] <https://vungle.com/> *Jun Zhu* >> > Sr. Engineer I, Data >> > ＋86 18565739171 >> > >> > [image: in1552694272.png] <https://www.linkedin.com/company/vungle> >> > [image: >> > fb1552694203.png] <https://facebook.com/vungle> [image: >> > tw1552694330.png] <https://twitter.com/vungle> [image: >> > ig1552694392.png] <https://www.instagram.com/vungle> >> > Units 3801, 3804, 38F, C Block, Beijing Yintai Center, Beijing, China >> > >> > > > -- > [image: vshapesaqua11553186012.gif] <https://vungle.com/> *Jun Zhu* > Sr. Engineer I, Data > ＋86 18565739171 > > [image: in1552694272.png] <https://www.linkedin.com/company/vungle> [image: > fb1552694203.png] <https://facebook.com/vungle> [image: > tw1552694330.png] <https://twitter.com/vungle> [image: > ig1552694392.png] <https://www.instagram.com/vungle> > Units 3801, 3804, 38F, C Block, Beijing Yintai Center, Beijing, China > >
