mkk1490 opened a new issue #3313: URL: https://github.com/apache/hudi/issues/3313
**_Tips before filing an issue_** - Have you gone through our [FAQs](https://cwiki.apache.org/confluence/display/HUDI/FAQ)? - Join the mailing list to engage in conversations and get faster support at [email protected]. - If you have triaged this as a bug, then file an [issue](https://issues.apache.org/jira/projects/HUDI/issues) directly. **Describe the problem you faced** A batch process with updates to the existing tables in Datalake. These are Hive external partitioned tables with location pointed to a s3 directory. I'm working on PoC to migrate all the tables to Hudi. I did a bulk_insert for IDL and everything went fine. For upserts, I have a problem. My primary key combo has a timestamp field in it. I have added all the required config in my code. Data are getting duplicated because of the timestamp field generating differently in the recordkey.field while upsert operation. Below are my hudi options: hudi_options = { 'hoodie.table.name': 'f_claim_mdcl_hudi_cow', 'hoodie.datasource.write.recordkey.field': 'claim_id,pat_id,claim_subm_dt,plac_of_srvc_cd,src_pri_psbr_id,src_plan_id' 'hoodie.datasource.write.partitionpath.field': 'src_sys_nm,yr_mth', 'hoodie.datasource.write.table.Type': 'COPY_ON_WRITE', 'hoodie.datasource.write.table.name': 'f_hudi_cow', # 'hoodie.combine.before.insert': 'false', 'hoodie.combine.before.upsert': 'true', 'hoodie.datasource.hive_sync.enable': 'true', 'hoodie.datasource.hive_sync.table': 'f_hudi_cow', 'hoodie.datasource.hive_sync.partition_fields': 'src_sys_nm,yr_mth', 'hoodie.datasource.hive_sync.partition_extractor_class': 'org.apache.hudi.hive.MultiPartKeysValueExtractor', 'hoodie.datasource.write.hive_style_partitioning': 'true', 'hoodie.datasource.hive_sync.database': 'us_commercial_datalake_app_commons_dev', 'hoodie.datasource.hive_sync.support_timestamp': 'true', 'hoodie.datasource.hive_sync.auto_create_db':'false', 'hoodie.datasource.write.keygenerator.class': 'org.apache.hudi.keygen.ComplexKeyGenerator', 'hoodie.datasource.write.row.writer.enable': 'true', 'hoodie.parquet.small.file.limit': '600000000', 'hoodie.parquet.max.file.size': '1000000000', 'hoodie.upsert.shuffle.parallelism': '10000', 'hoodie.insert.shuffle.parallelism': '10000', 'hoodie.clean.automatic': 'false', 'hoodie.cleaner.commits.retained': 3, 'hoodie.index.type': 'GLOBAL_SIMPLE', 'hoodie.simple.index.update.partition.path':'true', 'hoodie.metadata.enable': 'true' } df.write.format("org.apache.hudi"). \ options(**hudi_options).option('hoodie.datasource.write.operation', 'upsert'). \ mode("APPEND"). \ save("{s3_path}") I don't get any errors while processing. My record key for the bulk insert looks like this: claim_id:10420217599403398158,pat_id:8607357348,**claim_subm_dt:2020-11-21 00:00:00.0**,plac_of_srvc_cd:INPATIENT HOSPITAL,src_pri_psbr_id:7605954,src_plan_id:0009659999 record key for the upsert operation for the same record: claim_id:10420217599403398158,pat_id:8607357348,**claim_subm_dt:1605916800000000**,plac_of_srvc_cd:INPATIENT HOSPITAL,src_pri_psbr_id:7605954,src_plan_id:0009659999 **To Reproduce** Steps to reproduce the behavior: 1. Generate a set of records with timestamp as one of the primary keys in Hive external table stored on s3 2. Load the same set of records with mode("append") and option('hoodie.datasource.write.operation', 'upsert') 3. Check for duplicates excluding in the data **Expected behavior** No duplicates in the data. Recordkey.field to remain the same for timestamp field and not get converted to long **Environment Description** * Hudi version : 0.7.0 installed in EMR 5.33 * Spark version : 2.4.7 * Hive version : 2.3.7 * Hadoop version : Amazon 2.10.1 * Storage (HDFS/S3/GCS..) : s3 * Running on Docker? (yes/no) : No **Additional context** Add any other context about the problem here. **Stacktrace** ```Add the stacktrace of the error.``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
