Hi Satish, There are no parquet files? Can you share the full listing of files in the partition?
Thanks Vinoth On Mon, Apr 29, 2019 at 7:22 AM SATISH SIDNAKOPPA < [email protected]> wrote: > Yes, > As this needed discussion ,the thread was created in google groups for > inputs. > I am unable to read from rt table after multiple updates. > > 14:45 > /apps/hive/warehouse/emp_mor_26/2019/09/22/.278a46f9--87a_20190426144153.log.1 > -* has record that was updated in run 1* > 15:00 > /apps/hive/warehouse/emp_mor_26/2019/09/22/.278a46f9--87a_20190426144540.log.1 > - *has record that was updated in run 2 and run 3* > 14:41 /apps/hive/warehouse/emp_mor_26/2019/09/22/.hoodie_partition_metadata > 14:41 > /apps/hive/warehouse/emp_mor_26/2019/09/22/278a46f9--87a_0_20190426144153.parquet > > > > > On Sat, Apr 27, 2019 at 7:24 PM SATISH SIDNAKOPPA < > [email protected]> wrote: > > > No ,the issue is faced with rt table created by sync tool . > > > > On Fri 26 Apr, 2019, 11:53 PM Vinoth Chandar <[email protected] wrote: > > > >> once you registered the rt table, is this working now for you? > >> > >> On Fri, Apr 26, 2019 at 9:36 AM SATISH SIDNAKOPPA < > >> [email protected]> wrote: > >> > >> > I am querying real time view of the table. > >> > This table (emp_mor_26_rt) created after runsync tool. > >> > So the first updated record are fetched from log1 file. > >> > > >> > Only after third update both the updates are placed in log files. > >> > > >> > > >> > > >> > > >> > On Fri 26 Apr, 2019, 6:30 PM Vinoth Chandar <[email protected] wrote: > >> > > >> > > Looks like you are querying the RO table? If so, the query only hits > >> > > parquet file; which was probably generated during the first upsert > and > >> > all > >> > > others went to the log. Unless compaction runs, it wont show up on > ro > >> > table > >> > > > >> > > If you want the latest merged view you need to query the RT table. > >> > > > >> > > Does that sound applicable? > >> > > > >> > > > >> > > > >> > > On Fri, Apr 26, 2019 at 3:02 AM [email protected] < > >> > > [email protected]> wrote: > >> > > > >> > > > Writing hudi set as below > >> > > > > >> > > > ds.withColumn("emp_name",lit("upd1 > >> > > > > >> > > > >> > > >> > Emily")).withColumn("ts",current_timestamp).write.format("com.uber.hoodie") > >> > > > .option(HoodieWriteConfig.TABLE_NAME,"emp_mor_26") > >> > > > .option(DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY,"emp_id") > >> > > > > .option(DataSourceWriteOptions.STORAGE_TYPE_OPT_KEY,"MERGE_ON_READ") > >> > > > .option(DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY, > >> "part_by") > >> > > > .option("hoodie.upsert.shuffle.parallelism",4) > >> > > > .mode(SaveMode.Append) > >> > > > .save("/apps/hive/warehouse/emp_mor_26") > >> > > > > >> > > > > >> > > > 1st run - write record 1,"hudi_045",current_timestamp as ts > >> > > > read result -- 1, hudi_045 > >> > > > 2nd run - write record 1,"hudi_046",current_timestamp as ts > >> > > > read result -- 1,hudi_046 > >> > > > 3rd run -- write record 1, "hoodie_123",current_timestamp as ts > >> > > > read result --- 1,hudi_046 > >> > > > 4th run -- write record 1, "hdie_1232324",current_timestamp as ts > >> > > > read result --- 1,hudi_046 > >> > > > > >> > > > after multiple updates to same record , > >> > > > the generated log.1 has multiple instances of the same record. > >> > > > At this point the updated record is not fetched. > >> > > > > >> > > > 14:45 > >> > > > > >> > > > >> > > >> > /apps/hive/warehouse/emp_mor_26/2019/09/22/.278a46f9--87a_20190426144153.log.1 > >> > > > - has record that was updated in run 1 > >> > > > 15:00 > >> > > > > >> > > > >> > > >> > /apps/hive/warehouse/emp_mor_26/2019/09/22/.278a46f9--87a_20190426144540.log.1 > >> > > > - has record that was updated in run 2 and run 3 > >> > > > 14:41 > >> > > > /apps/hive/warehouse/emp_mor_26/2019/09/22/.hoodie_partition_metadata > >> > > > 14:41 > >> > > > > >> > > > >> > > >> > /apps/hive/warehouse/emp_mor_26/2019/09/22/278a46f9--87a_0_20190426144153.parquet > >> > > > > >> > > > > >> > > > So is there any compaction to be enabled before reading or while > >> > writing > >> > > . > >> > > > > >> > > > > >> > > > >> > > >> > > >
