You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@hudi.apache.org by "phantomcoder62 (via GitHub)" <gi...@apache.org> on 2023/02/24 11:25:54 UTC
[GitHub] [hudi] phantomcoder62 opened a new issue, #8040: [SUPPORT] Getting error when writing into HUDI table if schema changed (datatype changed / column dropped)
phantomcoder62 opened a new issue, #8040:
URL: https://github.com/apache/hudi/issues/8040
**Problem**
We were trying schema evolution in our MOR Hudi table and we are able to add new column but when we delete a column/change its type, it gives this error -
"py4j.protocol.Py4JJavaError: An error occurred while calling o130.save.
org.apache.parquet.io.InvalidRecordException: Parquet/Avro schema mismatch: Avro field 'deleted_column_name' not found
at org.apache.parquet.avro.AvroRecordConverter.getAvroField(AvroRecordConverter.java:221)"
We did more research on this issue as it was coming occasionally. But once it comes, the error continues for all the subsequent write operation on the hudi MOR table and we can't write anything on that hudi table.
So our finding is that schema evolution may work fine until compaction takes place. When compaction happens in MOR, it get some file with the deleted column and some without it (or different datatypes) and that is causing this issue. You can test this by keeping the compaction, min/max commit, cleaner commit retained configurations to low values in MOR.
**To Reproduce**
This is the code snippet. We are using Glue 4.0 and Hudi version 0.12.1. (Tried using EC2 as well)
import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from awsglue.context import GlueContext
from awsglue.job import Job
from pyspark.sql.session import SparkSession
args = getResolvedOptions(sys.argv, ['JOB_NAME','schema_evolution_testing'])
spark = SparkSession.builder.config('spark.serializer','org.apache.spark.serializer.KryoSerializer').config('spark.sql.hive.convertMetastoreParquet','false').getOrCreate()
sc = spark.sparkContext
glueContext = GlueContext(sc)
job = Job(glueContext)
job.init(args['JOB_NAME'], args)
def main():
# HUDI configuration
commonOptions = {
'hoodie.upsert.shuffle.parallelism': 200,
'hoodie.datasource.write.table.type': 'MERGE_ON_READ',
'hoodie.datasource.write.operation': 'upsert',
'hoodie.compact.inline': 'true',
'hoodie.compact.inline.max.delta.commits': 5,
'hoodie.keep.max.commits': 5,
'hoodie.keep.min.commits': 4,
'hoodie.datasource.write.precombine.field': 'cdc_timestamp',
'hoodie.cleaner.policy': 'KEEP_LATEST_COMMITS',
'hoodie.cleaner.commits.retained': 3,
'hoodie.datasource.write.keygenerator.class': 'org.apache.hudi.keygen.NonpartitionedKeyGenerator'
}
tableConfig = {
"hoodie.table.name": 'emp',
"hoodie.datasource.write.recordkey.field": 'id',
'hoodie.datasource.write.table.name': 'emp'
}
CombinedConfig = {**tableConfig, **commonOptions}
# Reading Parquet files from raw S3 DMS output
df = spark.read.parquet('s3://bucket/folder/emp/')
print("df schema is:",df.schema.simpleString())
df.show()
# Writing into hudi
(
df.write.format("org.apache.hudi")
.options(**CombinedConfig)
.mode("append")
.save(f"s3://hudi_bucket/hudi_folder/emp")
)
print("Upsertion into HUDI completed")
main()
job.commit()
These are the steps we followed for testing this issue -
**Column Type Changed :**
run 1 -
creation and insertion of 4000 records in hudi table emp with schema - struct<Op:string,cdc_timestamp:string,id:int,name:string>. This job was successful and it created a parquet file in hudi table
run 2 -
Altered emp table and added column mgr_id integer. Updated 4000 records. New schema is - struct<Op:string,cdc_timestamp:string,id:int,name:string,mgr_id:int>. This job was successful and it created a .log file in Hudi table.
run 3 -
Altered emp table changed type of mgr_id column from integer to character varying and updated 3000 records & inserted 5 records of mgr_id. New schema is - struct<Op:string,cdc_timestamp:string,id:int,name:string,mgr_id:string>. This job was successful and it created another .log file and another parquet file in Hudi table.
run 4 -
Updated one record in DB. This job was successful and it created another .log file.
run 5 -
Updated one record in DB. This job failed with this ERROR- An error occurred while calling o120.save. Found int, expecting union
Error log -
File "/tmp/schema_evolution_testing.py", line 51, in main
.save(hudi_table_path)
File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 968, in save
self._jwrite.save(path)
File "/opt/amazon/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in __call__
return_value = get_return_value(
File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 190, in deco
return f(*a, **kw)
File "/opt/amazon/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/protocol.py", line 326, in get_return_value
raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling o120.save.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 41.0 failed 4 times, most recent failure: Lost task 0.3 in stage 41.0 (TID 185) (172.34.225.30 executor 4): org.apache.hudi.exception.HoodieException: Exception when reading log file
at org.apache.hudi.common.table.log.AbstractHoodieLogRecordReader.scanInternal(AbstractHoodieLogRecordReader.java:352)
at org.apache.hudi.common.table.log.AbstractHoodieLogRecordReader.scan(AbstractHoodieLogRecordReader.java:192)
at org.apache.hudi.common.table.log.HoodieMergedLogRecordScanner.performScan(HoodieMergedLogRecordScanner.java:110)
at org.apache.hudi.common.table.log.HoodieMergedLogRecordScanner.<init>(HoodieMergedLogRecordScanner.java:103)
at org.apache.hudi.common.table.log.HoodieMergedLogRecordScanner$Builder.build(HoodieMergedLogRecordScanner.java:324)
at org.apache.hudi.table.action.compact.HoodieCompactor.compact(HoodieCompactor.java:198)
at org.apache.hudi.table.action.compact.HoodieCompactor.lambda$compact$57154431$1(HoodieCompactor.java:138)
at org.apache.spark.api.java.JavaPairRDD$.$anonfun$toScalaFunction$1(JavaPairRDD.scala:1070)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:455)
at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:480)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:486)
at org.apache.spark.storage.memory.MemoryStore.putIterator(MemoryStore.scala:223)
at org.apache.spark.storage.memory.MemoryStore.putIteratorAsBytes(MemoryStore.scala:352)
at org.apache.spark.storage.BlockManager.$anonfun$doPutIterator$1(BlockManager.scala:1525)
at org.apache.spark.storage.BlockManager.org$apache$spark$storage$BlockManager$$doPut(BlockManager.scala:1435)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1499)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:1322)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:376)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:327)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:138)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1516)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
Caused by: org.apache.avro.AvroTypeException: Found int, expecting union
at org.apache.avro.io.ResolvingDecoder.doAction(ResolvingDecoder.java:308)
at org.apache.avro.io.parsing.Parser.advance(Parser.java:86)
at org.apache.avro.io.ResolvingDecoder.readIndex(ResolvingDecoder.java:275)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:188)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:161)
at org.apache.avro.generic.GenericDatumReader.readField(GenericDatumReader.java:260)
at org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:248)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:180)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:161)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:154)
at org.apache.hudi.common.table.log.block.HoodieAvroDataBlock$RecordIterator.next(HoodieAvroDataBlock.java:207)
at org.apache.hudi.common.table.log.block.HoodieAvroDataBlock$RecordIterator.next(HoodieAvroDataBlock.java:144)
at org.apache.hudi.common.table.log.AbstractHoodieLogRecordReader.processDataBlock(AbstractHoodieLogRecordReader.java:382)
at org.apache.hudi.common.table.log.AbstractHoodieLogRecordReader.processQueuedBlocksForInstant(AbstractHoodieLogRecordReader.java:464)
at org.apache.hudi.common.table.log.AbstractHoodieLogRecordReader.scanInternal(AbstractHoodieLogRecordReader.java:343)
**Column dropped :**
run 1 -
creation and insertion of 35 records in hudi table emp with schema - struct<Op:string,cdc_timestamp:string,id:int,name:string,mgr_id:string>. This job was successful and it created a parquet file in hudi table bucket.
run 2 -
Altered emp table and dropped column mgr_id. Updated 35 records. New schema is - struct<Op:string,cdc_timestamp:string,id:int,name:string>. This job created 4 new parquet files in hudi table bucket and then failed with this error - An error occurred while calling o120.save. Parquet/Avro schema mismatch: Avro field 'mgr_id' not found.
Error log -
File "/tmp/schema_evolution_testing.py", line 51, in main
.save(hudi_table_path)
File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 968, in save
self._jwrite.save(path)
File "/opt/amazon/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", line 1321, in __call__
return_value = get_return_value(
File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 190, in deco
return f(*a, **kw)
File "/opt/amazon/spark/python/lib/py4j-0.10.9.5-src.zip/py4j/protocol.py", line 326, in get_return_value
raise Py4JJavaError(
py4j.protocol.Py4JJavaError: An error occurred while calling o120.save.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 16.0 failed 4 times, most recent failure: Lost task 0.3 in stage 16.0 (TID 120) (172.36.30.113 executor 5): org.apache.hudi.exception.HoodieUpsertException: Error upserting bucketType UPDATE for partition :0
at org.apache.hudi.table.action.commit.BaseSparkCommitActionExecutor.handleUpsertPartition(BaseSparkCommitActionExecutor.java:329)
at org.apache.hudi.table.action.commit.BaseSparkCommitActionExecutor.lambda$mapPartitionsAsRDD$a3ab3c4$1(BaseSparkCommitActionExecutor.java:244)
at org.apache.spark.api.java.JavaRDDLike.$anonfun$mapPartitionsWithIndex$1(JavaRDDLike.scala:102)
at org.apache.spark.api.java.JavaRDDLike.$anonfun$mapPartitionsWithIndex$1$adapted(JavaRDDLike.scala:102)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsWithIndex$2(RDD.scala:907)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsWithIndex$2$adapted(RDD.scala:907)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.$anonfun$getOrCompute$1(RDD.scala:378)
at org.apache.spark.storage.BlockManager.$anonfun$doPutIterator$1(BlockManager.scala:1525)
at org.apache.spark.storage.BlockManager.org$apache$spark$storage$BlockManager$$doPut(BlockManager.scala:1435)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1499)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:1322)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:376)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:327)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:138)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1516)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
Caused by: org.apache.hudi.exception.HoodieException: org.apache.hudi.exception.HoodieException: java.util.concurrent.ExecutionException: org.apache.hudi.exception.HoodieException: operation has failed
at org.apache.hudi.table.action.commit.HoodieMergeHelper.runMerge(HoodieMergeHelper.java:149)
at org.apache.hudi.table.action.commit.BaseSparkCommitActionExecutor.handleUpdateInternal(BaseSparkCommitActionExecutor.java:358)
at org.apache.hudi.table.action.commit.BaseSparkCommitActionExecutor.handleUpdate(BaseSparkCommitActionExecutor.java:349)
at org.apache.hudi.table.action.deltacommit.BaseSparkDeltaCommitActionExecutor.handleUpdate(BaseSparkDeltaCommitActionExecutor.java:80)
at org.apache.hudi.table.action.commit.BaseSparkCommitActionExecutor.handleUpsertPartition(BaseSparkCommitActionExecutor.java:322)
Caused by: org.apache.hudi.exception.HoodieException: java.util.concurrent.ExecutionException: org.apache.hudi.exception.HoodieException: operation has failed
at org.apache.hudi.common.util.queue.BoundedInMemoryExecutor.execute(BoundedInMemoryExecutor.java:161)
at org.apache.hudi.table.action.commit.HoodieMergeHelper.runMerge(HoodieMergeHelper.java:147)
Caused by: java.util.concurrent.ExecutionException: org.apache.hudi.exception.HoodieException: operation has failed
at java.util.concurrent.FutureTask.report(FutureTask.java:122)
at java.util.concurrent.FutureTask.get(FutureTask.java:192)
at org.apache.hudi.common.util.queue.BoundedInMemoryExecutor.execute(BoundedInMemoryExecutor.java:155)
Caused by: org.apache.hudi.exception.HoodieException: operation has failed
at org.apache.hudi.common.util.queue.BoundedInMemoryQueue.throwExceptionIfFailed(BoundedInMemoryQueue.java:248)
at org.apache.hudi.common.util.queue.BoundedInMemoryQueue.readNextRecord(BoundedInMemoryQueue.java:226)
at org.apache.hudi.common.util.queue.BoundedInMemoryQueue.access$100(BoundedInMemoryQueue.java:52)
at org.apache.hudi.common.util.queue.BoundedInMemoryQueue$QueueIterator.hasNext(BoundedInMemoryQueue.java:278)
at org.apache.hudi.common.util.queue.BoundedInMemoryQueueConsumer.consume(BoundedInMemoryQueueConsumer.java:36)
at org.apache.hudi.common.util.queue.BoundedInMemoryExecutor.lambda$null$2(BoundedInMemoryExecutor.java:135)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
Caused by: org.apache.hudi.exception.HoodieException: unable to read next record from parquet file
at org.apache.hudi.common.util.ParquetReaderIterator.hasNext(ParquetReaderIterator.java:53)
at org.apache.hudi.common.util.queue.IteratorBasedQueueProducer.produce(IteratorBasedQueueProducer.java:45)
at org.apache.hudi.common.util.queue.BoundedInMemoryExecutor.lambda$null$0(BoundedInMemoryExecutor.java:106)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
Caused by: org.apache.parquet.io.InvalidRecordException: Parquet/Avro schema mismatch: Avro field 'mgr_id' not found
at org.apache.parquet.avro.AvroRecordConverter.getAvroField(AvroRecordConverter.java:221)
at org.apache.parquet.avro.AvroRecordConverter.<init>(AvroRecordConverter.java:126)
at org.apache.parquet.avro.AvroRecordConverter.<init>(AvroRecordConverter.java:91)
at org.apache.parquet.avro.AvroRecordMaterializer.<init>(AvroRecordMaterializer.java:33)
at org.apache.parquet.avro.AvroReadSupport.prepareForRead(AvroReadSupport.java:142)
at org.apache.parquet.hadoop.InternalParquetRecordReader.initialize(InternalParquetRecordReader.java:185)
at org.apache.parquet.hadoop.ParquetReader.initReader(ParquetReader.java:156)
at org.apache.parquet.hadoop.ParquetReader.read(ParquetReader.java:135)
at org.apache.hudi.common.util.ParquetReaderIterator.hasNext(ParquetReaderIterator.java:48)
This script has same behavior on AWS EC2 as well where our production code is running for same HUDI Version 0.12.1.
**Environment Description**
* Hudi version : 0.12.1
* Spark version : 3.3
* Storage (HDFS/S3/GCS..) : S3
* Platform : Glue 4.0 and EC2
* Running on Docker? (yes/no) : No
--
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: commits-unsubscribe@hudi.apache.org.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1468097577
any updates ?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] PhantomHunt commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "PhantomHunt (via GitHub)" <gi...@apache.org>.
PhantomHunt commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499520663
> > Can you try adding these configurations to enable Hudi's full schema evolution? From the configurations, i think Avro's schema resolution was used for schema evolution.
> > ```
> > "hoodie.schema.on.read.enable" -> "true",
> > "hoodie.datasource.write.reconcile.schema" -> "true"
> > ```
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > If it still doesn't work, is it possible to provide a minimal example so that we can try reproducing on our end? Thank you
>
> Hi, I tested this configuration, and now the error is not coming up. Will do some in-depth testing next week. I also did some research and figured out there are more such configurations available now like -
>
> ```
> 'hoodie.datasource.write.schema.allow.auto.evolution.column.drop' : 'true',
> 'hoodie.avro.schema.external.transformation' : 'true',
> 'hoodie.avro.schema.validate' : 'true'
> ```
>
> So what is the difference between the configurations you gave vs these? Which configuration is the best one here?
@voonhous any update on this?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] voonhous commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "voonhous (via GitHub)" <gi...@apache.org>.
voonhous commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497673600
Apologies, can't help you with this since this seems to be a AWS glue issue.
However, @PhantomHunt's issue doesn't seem related to this.
> Note - Now we are using a python script on AWS EC2 for writing into HUDI and not AWS Glue.
In this regard, can you please share a minimal example of your code that is triggering this issue?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] PhantomHunt commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "PhantomHunt (via GitHub)" <gi...@apache.org>.
PhantomHunt commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499466468
> Can you try adding these configurations to enable Hudi's full schema evolution? From the configurations, i think Avro's schema resolution was used for schema evolution.
>
> ```
> "hoodie.schema.on.read.enable" -> "true",
> "hoodie.datasource.write.reconcile.schema" -> "true"
> ```
>
> If it still doesn't work, is it possible to provide a minimal example so that we can try reproducing on our end? Thank you
Hi, I tested this configuration, and now the error is not coming up. Will do some in-depth testing next week. I also did some research and figured out there are more such configurations available now -
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] voonhous commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "voonhous (via GitHub)" <gi...@apache.org>.
voonhous commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499495444
It's best practice to have 1 issue tracking 1 problem. Given that OP's issue isn't related to Glue, a new ticket might be helpful for future users encountering Glue + schema evolution issues...
I don't know, just my 2c.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1496629170
I've just posted this in Slack; ideally, we can reach an agreement sooner on this issue
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499485442
same error
```
try:
import sys
import os
from pyspark.context import SparkContext
from pyspark.sql.session import SparkSession
from awsglue.context import GlueContext
from awsglue.job import Job
from awsglue.dynamicframe import DynamicFrame
from pyspark.sql.functions import col, to_timestamp, monotonically_increasing_id, to_date, when
from pyspark.sql.functions import *
from awsglue.utils import getResolvedOptions
from pyspark.sql.types import *
from datetime import datetime, date
import boto3
from functools import reduce
from pyspark.sql import Row
import uuid
from faker import Faker
except Exception as e:
print("Modules are missing : {} ".format(e))
spark = (SparkSession.builder.config('spark.serializer', 'org.apache.spark.serializer.KryoSerializer') \
.config('spark.sql.hive.convertMetastoreParquet', 'false') \
.config('spark.sql.catalog.spark_catalog', 'org.apache.spark.sql.hudi.catalog.HoodieCatalog') \
.config('spark.sql.extensions', 'org.apache.spark.sql.hudi.HoodieSparkSessionExtension') \
.config('spark.sql.legacy.pathOptionBehavior.enabled', 'true').getOrCreate())
sc = spark.sparkContext
glueContext = GlueContext(sc)
job = Job(glueContext)
logger = glueContext.get_logger()
# =================================INSERTING DATA =====================================
global faker
faker = Faker()
class DataGenerator(object):
@staticmethod
def get_data():
return [
(
uuid.uuid4().__str__(),
faker.name(),
faker.random_element(elements=('IT', 'HR', 'Sales', 'Marketing')),
faker.random_element(elements=('CA', 'NY', 'TX', 'FL', 'IL', 'RJ')),
str(faker.random_int(min=10000, max=150000)),
str(faker.random_int(min=18, max=60)),
str(faker.random_int(min=0, max=100000)),
str(faker.unix_time()),
faker.email(),
faker.credit_card_number(card_type='amex'),
) for x in range(100)
]
data = DataGenerator.get_data()
columns = ["emp_id", "employee_name", "department", "state", "salary", "age", "bonus", "ts", "email", "credit_card"]
spark_df = spark.createDataFrame(data=data, schema=columns)
# ============================== Settings =======================================
db_name = "hudidb"
table_name = "employees"
recordkey = 'emp_id'
precombine = "ts"
PARTITION_FIELD = 'state'
path = "s3://hudi-demos-emr-serverless-project-soumil/tmp1/"
method = 'upsert'
table_type = "MERGE_ON_READ"
# ====================================================================================
hudi_part_write_config = {
'className': 'org.apache.hudi',
"hoodie.schema.on.read.enable":"true",
"hoodie.datasource.write.reconcile.schema":"true",
"hoodie.avro.schema.external.transformation":"true",
'hoodie.avro.schema.validate':"true",
"hoodie.datasource.write.schema.allow.auto.evolution.column.drop":"true",
'hoodie.table.name': table_name,
'hoodie.datasource.write.table.type': table_type,
'hoodie.datasource.write.operation': method,
'hoodie.datasource.write.recordkey.field': recordkey,
'hoodie.datasource.write.precombine.field': precombine,
'hoodie.datasource.hive_sync.mode': 'hms',
'hoodie.datasource.hive_sync.enable': 'true',
'hoodie.datasource.hive_sync.use_jdbc': 'false',
'hoodie.datasource.hive_sync.support_timestamp': 'false',
'hoodie.datasource.hive_sync.database': db_name,
'hoodie.datasource.hive_sync.table': table_name,
}
spark_df.write.format("hudi").options(**hudi_part_write_config).mode("append").save(path)
# ================================================================
# Adding NEW COLUMN
# ================================================================
class DataGenerator(object):
@staticmethod
def get_data():
return [
(
uuid.uuid4().__str__(),
faker.name(),
faker.random_element(elements=('IT', 'HR', 'Sales', 'Marketing')),
faker.random_element(elements=('CA', 'NY', 'TX', 'FL', 'IL', 'RJ')),
str(faker.random_int(min=10000, max=150000)),
str(faker.random_int(min=18, max=60)),
str(faker.random_int(min=0, max=100000)),
str(faker.unix_time()),
faker.email(),
faker.credit_card_number(card_type='amex'),
faker.date().__str__()
) for x in range(100)
]
data = DataGenerator.get_data()
columns = ["emp_id", "employee_name", "department", "state", "salary", "age", "bonus", "ts", "email", "credit_card",
"new_date_col"]
spark_df = spark.createDataFrame(data=data, schema=columns)
spark_df.write.format("hudi").options(**hudi_part_write_config).mode("append").save(path)
try:
print("Try1")
table_name_test = f"{table_name}_ro"
query = f"alter table {db_name}.{table_name_test} drop column credit_card"
spark.sql(query)
except Exception as e:
print("ERR1", e)
try:
print("Try2")
table_name_test = f"{table_name}_rt"
query = f"alter table {db_name}.{table_name_test} drop column credit_card"
spark.sql(query)
except Exception as e:
print("ERR2", e)
```
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499490531
I'll have to explain everything from scratch, however I recommend leaving the github issue open as long as the problem persists.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] easonwood commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "easonwood (via GitHub)" <gi...@apache.org>.
easonwood commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1518427810
https://github.com/apache/hudi/issues/8540
Hi,
Can we check this similar ticket ?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] voonhous commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "voonhous (via GitHub)" <gi...@apache.org>.
voonhous commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497305151
Can you try adding these configurations to enable Hudi's full schema evolution? From the configuration, i think Avro's schema resolution was used for schema evolution.
```
"hoodie.schema.on.read.enable" -> "true",
"hoodie.datasource.write.reconcile.schema" -> "true"
```
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] voonhous commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "voonhous (via GitHub)" <gi...@apache.org>.
voonhous commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497413435
I'm not really familiar with AWS's product, but it looks like HoodieSparkSessionExtension isn't being used here.
Is this in your job params?
```
--conf spark.sql.extensions=org.apache.spark.sql.hudi.HoodieSparkSessionExtension
```
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] nfarah86 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "nfarah86 (via GitHub)" <gi...@apache.org>.
nfarah86 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1496816796
flagging.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1449118130
i think we need to ask AWS to update Hudi version to 0.13
let see what other have to say on this
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497479847
let me try with setting you mentioned
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] voonhous commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "voonhous (via GitHub)" <gi...@apache.org>.
voonhous commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499531113
@PhantomHunt Will check and get back to you on Monday.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] phantomcoder62 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "phantomcoder62 (via GitHub)" <gi...@apache.org>.
phantomcoder62 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1448021928
> sample code
>
> ```
> import sys
> from awsglue.transforms import *
> from awsglue.utils import getResolvedOptions
> from pyspark.sql.session import SparkSession
> from pyspark.context import SparkContext
> from awsglue.context import GlueContext
> from awsglue.job import Job
> from pyspark.sql import DataFrame, Row
> from pyspark.sql.functions import *
> from pyspark.sql.functions import col, to_timestamp, monotonically_increasing_id, to_date, when
> import datetime
> from awsglue import DynamicFrame
>
> import boto3
>
> ## @params: [JOB_NAME]
> args = getResolvedOptions(sys.argv,
> ["JOB_NAME", "database_name", "kinesis_table_name", "starting_position_of_kinesis_iterator",
> "hudi_table_name", "window_size", "s3_path_hudi", "s3_path_spark"])
>
> spark = SparkSession.builder.config('spark.serializer', 'org.apache.spark.serializer.KryoSerializer').config(
> 'spark.sql.hive.convertMetastoreParquet', 'false').getOrCreate()
>
> sc = spark.sparkContext
> glueContext = GlueContext(sc)
> job = Job(glueContext)
> job.init(args['JOB_NAME'], args)
>
> database_name = args["database_name"]
> kinesis_table_name = args["kinesis_table_name"]
> hudi_table_name = args["hudi_table_name"]
> s3_path_hudi = args["s3_path_hudi"]
> s3_path_spark = args["s3_path_spark"]
>
> print("***********")
> print(f"""
> database_name {database_name}
> kinesis_table_name = {kinesis_table_name}
> hudi_table_name ={hudi_table_name}
> s3_path_hudi = {s3_path_hudi}
> s3_path_spark = {s3_path_spark}
> """)
> # can be set to "latest", "trim_horizon" or "earliest"
> starting_position_of_kinesis_iterator = args["starting_position_of_kinesis_iterator"]
>
> # The amount of time to spend processing each batch
> window_size = args["window_size"]
>
> data_frame_DataSource0 = glueContext.create_data_frame.from_catalog(
> database=database_name,
> table_name=kinesis_table_name,
> transformation_ctx="DataSource0",
> additional_options={"inferSchema": "true", "startingPosition": starting_position_of_kinesis_iterator}
> )
>
> # config
> commonConfig = {
> 'path': s3_path_hudi
> }
>
> hudiWriteConfig = {
> 'className': 'org.apache.hudi',
> 'hoodie.table.name': hudi_table_name,
> 'hoodie.datasource.write.operation': 'upsert',
> 'hoodie.datasource.write.table.type': 'COPY_ON_WRITE',
> 'hoodie.datasource.write.precombine.field': 'date',
> 'hoodie.datasource.write.recordkey.field': '_id',
> 'hoodie.datasource.write.partitionpath.field': 'year:SIMPLE,month:SIMPLE,day:SIMPLE',
> 'hoodie.datasource.write.keygenerator.class': 'org.apache.hudi.keygen.CustomKeyGenerator',
> 'hoodie.deltastreamer.keygen.timebased.timestamp.type': 'MIXED',
> 'hoodie.deltastreamer.keygen.timebased.input.dateformat': 'yyyy-mm-dd',
> 'hoodie.deltastreamer.keygen.timebased.output.dateformat': 'yyyy/MM/dd'
> }
>
> hudiGlueConfig = {
> 'hoodie.datasource.hive_sync.enable': 'true',
> 'hoodie.datasource.hive_sync.sync_as_datasource': 'false',
> 'hoodie.datasource.hive_sync.database': database_name,
> 'hoodie.datasource.hive_sync.table': hudi_table_name,
> 'hoodie.datasource.hive_sync.use_jdbc': 'false',
> 'hoodie.datasource.write.hive_style_partitioning': 'true',
> 'hoodie.datasource.hive_sync.partition_extractor_class': 'org.apache.hudi.hive.MultiPartKeysValueExtractor',
> 'hoodie.datasource.hive_sync.partition_fields': 'year,month,day'
> }
>
> combinedConf = {
> **commonConfig,
> **hudiWriteConfig,
> **hudiGlueConfig
> }
>
>
> # ensure the incomong record has the correct current schema, new fresh columns are fine, if a column exists in current schema but not in incoming record then manually add before inserting
> def evolveSchema(kinesis_df, table, forcecast=False):
> try:
> # get existing table's schema
> glue_catalog_df = spark.sql("SELECT * FROM " + table + " LIMIT 0")
> # sanitize for hudi specific system columns
> columns_to_drop = ['_hoodie_commit_time', '_hoodie_commit_seqno', '_hoodie_record_key',
> '_hoodie_partition_path', '_hoodie_file_name']
> glue_catalog_df_sanitized = glue_catalog_df.drop(*columns_to_drop)
> if (kinesis_df.schema != glue_catalog_df_sanitized.schema):
> merged_df = kinesis_df.unionByName(glue_catalog_df_sanitized, allowMissingColumns=True)
> return (merged_df)
> except Exception as e:
> print(e)
> return (kinesis_df)
>
>
> def processBatch(data_frame, batchId):
> if (data_frame.count() > 0):
> kinesis_dynamic_frame = DynamicFrame.fromDF(data_frame, glueContext, "from_kinesis_data_frame")
> kinesis_data_frame = kinesis_dynamic_frame.toDF()
>
> kinesis_data_frame = evolveSchema(kinesis_data_frame, database_name + '.' + hudi_table_name, False)
>
> glueContext.write_dynamic_frame.from_options(
> frame=DynamicFrame.fromDF(kinesis_data_frame, glueContext, "evolved_kinesis_data_frame"),
> connection_type="custom.spark",
> connection_options=combinedConf
> )
>
>
> glueContext.forEachBatch(
> frame=data_frame_DataSource0,
> batch_function=processBatch,
> options={
> "windowSize": window_size,
> "checkpointLocation": s3_path_spark
> }
> )
>
> job.commit()
> ```
Soumil this solution is **incorrect** for our problem and absolutely **useless** for our use case as the logic here is for COW HUDI table and will not work for **MOR tables** as the compaction in MOR works differently. You are merging old data in HUDI and creating a new dataframe without the deleted column and pushing in COW HUDI table here and it will work for COW as in COW new parquets are created. But in MOR, a .log file is created in every iteration and during compaction the old data is merged and parquet is created. Still we tested the code you gave us and as expected, we are getting the same error once compaction happens.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1479436579
Hello do we have an update for this issue ?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] PhantomHunt commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "PhantomHunt (via GitHub)" <gi...@apache.org>.
PhantomHunt commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1495575800
> i think we need to ask AWS to update Hudi version to 0.13 let see what other have to say on this
I tested it and found that the issue I am facing still exists for HUDI 0.13.0 . We are getting the same error when the compaction runs on the MOR table. Changing column type and deleting a column in a MOR hudi table is a very important feature we need.
Note - Now we are using a python script on AWS EC2 for writing into HUDI and not AWS Glue.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] phantomcoder62 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "phantomcoder62 (via GitHub)" <gi...@apache.org>.
phantomcoder62 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1448023666
> please share your job parameters
We are running our production code for Hudi upsert on EC2. We are not using any job parameter for that. In AWS glue, we are using the configuration --datalake-formats having value 'hudi'
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1449098572
i think i have tried deleting column with glue 4.0 and table type as MOR
i am getting following error
# Code to other can replicate
```
try:
import sys
import os
from pyspark.context import SparkContext
from pyspark.sql.session import SparkSession
from awsglue.context import GlueContext
from awsglue.job import Job
from awsglue.dynamicframe import DynamicFrame
from pyspark.sql.functions import col, to_timestamp, monotonically_increasing_id, to_date, when
from pyspark.sql.functions import *
from awsglue.utils import getResolvedOptions
from pyspark.sql.types import *
from datetime import datetime, date
import boto3
from functools import reduce
from pyspark.sql import Row
import uuid
from faker import Faker
except Exception as e:
print("Modules are missing : {} ".format(e))
spark = (SparkSession.builder.config('spark.serializer', 'org.apache.spark.serializer.KryoSerializer') \
.config('spark.sql.hive.convertMetastoreParquet', 'false') \
.config('spark.sql.catalog.spark_catalog', 'org.apache.spark.sql.hudi.catalog.HoodieCatalog') \
.config('spark.sql.extensions', 'org.apache.spark.sql.hudi.HoodieSparkSessionExtension') \
.config('spark.sql.legacy.pathOptionBehavior.enabled', 'true').getOrCreate())
sc = spark.sparkContext
glueContext = GlueContext(sc)
job = Job(glueContext)
logger = glueContext.get_logger()
# =================================INSERTING DATA =====================================
global faker
faker = Faker()
class DataGenerator(object):
@staticmethod
def get_data():
return [
(
uuid.uuid4().__str__(),
faker.name(),
faker.random_element(elements=('IT', 'HR', 'Sales', 'Marketing')),
faker.random_element(elements=('CA', 'NY', 'TX', 'FL', 'IL', 'RJ')),
str(faker.random_int(min=10000, max=150000)),
str(faker.random_int(min=18, max=60)),
str(faker.random_int(min=0, max=100000)),
str(faker.unix_time()),
faker.email(),
faker.credit_card_number(card_type='amex'),
) for x in range(100)
]
data = DataGenerator.get_data()
columns = ["emp_id", "employee_name", "department", "state", "salary", "age", "bonus", "ts", "email", "credit_card"]
spark_df = spark.createDataFrame(data=data, schema=columns)
# ============================== Settings =======================================
db_name = "hudidb"
table_name = "employees"
recordkey = 'emp_id'
precombine = "ts"
PARTITION_FIELD = 'state'
path = "s3://hudi-demos-emr-serverless-project-soumil/tmp1/"
method = 'upsert'
table_type = "MERGE_ON_READ"
# ====================================================================================
hudi_part_write_config = {
'className': 'org.apache.hudi',
'hoodie.table.name': table_name,
'hoodie.datasource.write.table.type': table_type,
'hoodie.datasource.write.operation': method,
'hoodie.datasource.write.recordkey.field': recordkey,
'hoodie.datasource.write.precombine.field': precombine,
'hoodie.datasource.hive_sync.mode': 'hms',
'hoodie.datasource.hive_sync.enable': 'true',
'hoodie.datasource.hive_sync.use_jdbc': 'false',
'hoodie.datasource.hive_sync.support_timestamp': 'false',
'hoodie.datasource.hive_sync.database': db_name,
'hoodie.datasource.hive_sync.table': table_name,
}
spark_df.write.format("hudi").options(**hudi_part_write_config).mode("append").save(path)
# ================================================================
# Adding NEW COLUMN
# ================================================================
class DataGenerator(object):
@staticmethod
def get_data():
return [
(
uuid.uuid4().__str__(),
faker.name(),
faker.random_element(elements=('IT', 'HR', 'Sales', 'Marketing')),
faker.random_element(elements=('CA', 'NY', 'TX', 'FL', 'IL', 'RJ')),
str(faker.random_int(min=10000, max=150000)),
str(faker.random_int(min=18, max=60)),
str(faker.random_int(min=0, max=100000)),
str(faker.unix_time()),
faker.email(),
faker.credit_card_number(card_type='amex'),
faker.date().__str__()
) for x in range(100)
]
data = DataGenerator.get_data()
columns = ["emp_id", "employee_name", "department", "state", "salary", "age", "bonus", "ts", "email", "credit_card",
"new_date_col"]
spark_df = spark.createDataFrame(data=data, schema=columns)
spark_df.write.format("hudi").options(**hudi_part_write_config).mode("append").save(path)
try:
print("Try1")
table_name_test = f"{table_name}_ro"
query = f"alter table {db_name}.{table_name_test} drop column credit_card"
spark.sql(query)
except Exception as e:
print("ERR1", e)
try:
print("Try2")
table_name_test = f"{table_name}_rt"
query = f"alter table {db_name}.{table_name_test} drop column credit_card"
spark.sql(query)
except Exception as e:
print("ERR2", e)
```
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497905919
I'm not sure if the problem is with HUDI or AWS, but in either case, we need to find a solution so that customers can delete columns when using table type as MOR
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1443831871
sample code
```
import sys
from awsglue.transforms import *
from awsglue.utils import getResolvedOptions
from pyspark.sql.session import SparkSession
from pyspark.context import SparkContext
from awsglue.context import GlueContext
from awsglue.job import Job
from pyspark.sql import DataFrame, Row
from pyspark.sql.functions import *
from pyspark.sql.functions import col, to_timestamp, monotonically_increasing_id, to_date, when
import datetime
from awsglue import DynamicFrame
import boto3
## @params: [JOB_NAME]
args = getResolvedOptions(sys.argv,
["JOB_NAME", "database_name", "kinesis_table_name", "starting_position_of_kinesis_iterator",
"hudi_table_name", "window_size", "s3_path_hudi", "s3_path_spark"])
spark = SparkSession.builder.config('spark.serializer', 'org.apache.spark.serializer.KryoSerializer').config(
'spark.sql.hive.convertMetastoreParquet', 'false').getOrCreate()
sc = spark.sparkContext
glueContext = GlueContext(sc)
job = Job(glueContext)
job.init(args['JOB_NAME'], args)
database_name = args["database_name"]
kinesis_table_name = args["kinesis_table_name"]
hudi_table_name = args["hudi_table_name"]
s3_path_hudi = args["s3_path_hudi"]
s3_path_spark = args["s3_path_spark"]
print("***********")
print(f"""
database_name {database_name}
kinesis_table_name = {kinesis_table_name}
hudi_table_name ={hudi_table_name}
s3_path_hudi = {s3_path_hudi}
s3_path_spark = {s3_path_spark}
""")
# can be set to "latest", "trim_horizon" or "earliest"
starting_position_of_kinesis_iterator = args["starting_position_of_kinesis_iterator"]
# The amount of time to spend processing each batch
window_size = args["window_size"]
data_frame_DataSource0 = glueContext.create_data_frame.from_catalog(
database=database_name,
table_name=kinesis_table_name,
transformation_ctx="DataSource0",
additional_options={"inferSchema": "true", "startingPosition": starting_position_of_kinesis_iterator}
)
# config
commonConfig = {
'path': s3_path_hudi
}
hudiWriteConfig = {
'className': 'org.apache.hudi',
'hoodie.table.name': hudi_table_name,
'hoodie.datasource.write.operation': 'upsert',
'hoodie.datasource.write.table.type': 'COPY_ON_WRITE',
'hoodie.datasource.write.precombine.field': 'date',
'hoodie.datasource.write.recordkey.field': '_id',
'hoodie.datasource.write.partitionpath.field': 'year:SIMPLE,month:SIMPLE,day:SIMPLE',
'hoodie.datasource.write.keygenerator.class': 'org.apache.hudi.keygen.CustomKeyGenerator',
'hoodie.deltastreamer.keygen.timebased.timestamp.type': 'MIXED',
'hoodie.deltastreamer.keygen.timebased.input.dateformat': 'yyyy-mm-dd',
'hoodie.deltastreamer.keygen.timebased.output.dateformat': 'yyyy/MM/dd'
}
hudiGlueConfig = {
'hoodie.datasource.hive_sync.enable': 'true',
'hoodie.datasource.hive_sync.sync_as_datasource': 'false',
'hoodie.datasource.hive_sync.database': database_name,
'hoodie.datasource.hive_sync.table': hudi_table_name,
'hoodie.datasource.hive_sync.use_jdbc': 'false',
'hoodie.datasource.write.hive_style_partitioning': 'true',
'hoodie.datasource.hive_sync.partition_extractor_class': 'org.apache.hudi.hive.MultiPartKeysValueExtractor',
'hoodie.datasource.hive_sync.partition_fields': 'year,month,day'
}
combinedConf = {
**commonConfig,
**hudiWriteConfig,
**hudiGlueConfig
}
# ensure the incomong record has the correct current schema, new fresh columns are fine, if a column exists in current schema but not in incoming record then manually add before inserting
def evolveSchema(kinesis_df, table, forcecast=False):
try:
# get existing table's schema
glue_catalog_df = spark.sql("SELECT * FROM " + table + " LIMIT 0")
# sanitize for hudi specific system columns
columns_to_drop = ['_hoodie_commit_time', '_hoodie_commit_seqno', '_hoodie_record_key',
'_hoodie_partition_path', '_hoodie_file_name']
glue_catalog_df_sanitized = glue_catalog_df.drop(*columns_to_drop)
if (kinesis_df.schema != glue_catalog_df_sanitized.schema):
merged_df = kinesis_df.unionByName(glue_catalog_df_sanitized, allowMissingColumns=True)
return (merged_df)
except Exception as e:
print(e)
return (kinesis_df)
def processBatch(data_frame, batchId):
if (data_frame.count() > 0):
kinesis_dynamic_frame = DynamicFrame.fromDF(data_frame, glueContext, "from_kinesis_data_frame")
kinesis_data_frame = kinesis_dynamic_frame.toDF()
kinesis_data_frame = evolveSchema(kinesis_data_frame, database_name + '.' + hudi_table_name, False)
glueContext.write_dynamic_frame.from_options(
frame=DynamicFrame.fromDF(kinesis_data_frame, glueContext, "evolved_kinesis_data_frame"),
connection_type="custom.spark",
connection_options=combinedConf
)
glueContext.forEachBatch(
frame=data_frame_DataSource0,
batch_function=processBatch,
options={
"windowSize": window_size,
"checkpointLocation": s3_path_spark
}
)
job.commit()
```
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497383266
The complete example is provided above; if you require more details, please let me know.
# Code
```
"""
--conf spark.serializer=org.apache.spark.serializer.KryoSerializer --conf spark.sql.hive.convertMetastoreParquet=false --conf spark.sql.hive.convertMetastoreParquet=false --conf spark.sql.catalog.spark_catalog=org.apache.spark.sql.hudi.catalog.HoodieCatalog --conf spark.sql.legacy.pathOptionBehavior.enabled=true
"""
try:
import sys
import os
from pyspark.context import SparkContext
from pyspark.sql.session import SparkSession
from awsglue.context import GlueContext
from awsglue.job import Job
from awsglue.dynamicframe import DynamicFrame
from pyspark.sql.functions import col, to_timestamp, monotonically_increasing_id, to_date, when
from pyspark.sql.functions import *
from awsglue.utils import getResolvedOptions
from pyspark.sql.types import *
from datetime import datetime, date
import boto3
from functools import reduce
from pyspark.sql import Row
import uuid
from faker import Faker
except Exception as e:
print("Modules are missing : {} ".format(e))
spark = (SparkSession.builder.config('spark.serializer', 'org.apache.spark.serializer.KryoSerializer') \
.config('spark.sql.hive.convertMetastoreParquet', 'false') \
.config('spark.sql.catalog.spark_catalog', 'org.apache.spark.sql.hudi.catalog.HoodieCatalog') \
.config('spark.sql.extensions', 'org.apache.spark.sql.hudi.HoodieSparkSessionExtension') \
.config('spark.sql.legacy.pathOptionBehavior.enabled', 'true').getOrCreate())
sc = spark.sparkContext
glueContext = GlueContext(sc)
job = Job(glueContext)
logger = glueContext.get_logger()
# =================================INSERTING DATA =====================================
global faker
faker = Faker()
class DataGenerator(object):
@staticmethod
def get_data():
return [
(
uuid.uuid4().__str__(),
faker.name(),
faker.random_element(elements=('IT', 'HR', 'Sales', 'Marketing')),
faker.random_element(elements=('CA', 'NY', 'TX', 'FL', 'IL', 'RJ')),
str(faker.random_int(min=10000, max=150000)),
str(faker.random_int(min=18, max=60)),
str(faker.random_int(min=0, max=100000)),
str(faker.unix_time()),
faker.email(),
faker.credit_card_number(card_type='amex'),
) for x in range(100)
]
data = DataGenerator.get_data()
columns = ["emp_id", "employee_name", "department", "state", "salary", "age", "bonus", "ts", "email", "credit_card"]
spark_df = spark.createDataFrame(data=data, schema=columns)
# ============================== Settings =======================================
db_name = "hudidb"
table_name = "employees"
recordkey = 'emp_id'
precombine = "ts"
PARTITION_FIELD = 'state'
path = "s3://hudi-demos-emr-serverless-project-soumil/tmp1/"
method = 'upsert'
table_type = "MERGE_ON_READ"
# ====================================================================================
hudi_part_write_config = {
'className': 'org.apache.hudi',
'hoodie.table.name': table_name,
'hoodie.datasource.write.table.type': table_type,
'hoodie.datasource.write.operation': method,
'hoodie.datasource.write.recordkey.field': recordkey,
'hoodie.datasource.write.precombine.field': precombine,
"hoodie.schema.on.read.enable":"true",
"hoodie.datasource.write.reconcile.schema":"true",
'hoodie.datasource.hive_sync.mode': 'hms',
'hoodie.datasource.hive_sync.enable': 'true',
'hoodie.datasource.hive_sync.use_jdbc': 'false',
'hoodie.datasource.hive_sync.support_timestamp': 'false',
'hoodie.datasource.hive_sync.database': db_name,
'hoodie.datasource.hive_sync.table': table_name,
}
spark_df.write.format("hudi").options(**hudi_part_write_config).mode("append").save(path)
# ================================================================
# Adding NEW COLUMN
# ================================================================
class DataGenerator(object):
@staticmethod
def get_data():
return [
(
uuid.uuid4().__str__(),
faker.name(),
faker.random_element(elements=('IT', 'HR', 'Sales', 'Marketing')),
faker.random_element(elements=('CA', 'NY', 'TX', 'FL', 'IL', 'RJ')),
str(faker.random_int(min=10000, max=150000)),
str(faker.random_int(min=18, max=60)),
str(faker.random_int(min=0, max=100000)),
str(faker.unix_time()),
faker.email(),
faker.credit_card_number(card_type='amex'),
faker.date().__str__()
) for x in range(100)
]
data = DataGenerator.get_data()
columns = ["emp_id", "employee_name", "department", "state", "salary", "age", "bonus", "ts", "email", "credit_card",
"new_date_col"]
spark_df = spark.createDataFrame(data=data, schema=columns)
spark_df.write.format("hudi").options(**hudi_part_write_config).mode("append").save(path)
try:
print("Try1")
table_name_test = f"{table_name}_ro"
query = f"alter table {db_name}.{table_name_test} drop column credit_card"
spark.sql(query)
except Exception as e:
print("ERR1", e)
try:
print("Try2")
table_name_test = f"{table_name}_rt"
query = f"alter table {db_name}.{table_name_test} drop column credit_card"
spark.sql(query)
except Exception as e:
print("ERR2", e)
```
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] PhantomHunt commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "PhantomHunt (via GitHub)" <gi...@apache.org>.
PhantomHunt commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499481865
> > ie.schema.on.read.enable" -> "true",
> > "hoodie.datasource.write.reconcile.schema" -> "true"
>
> were you able to delete the column in glue ?
Not in Glue, we are using writer script in EC2 which is not giving schema error now as it was giving previously. When I checked the _rt and _ro tables on Athena, found that table still contain those columns but no data there. That fits our use case as of now. Will check next week what is the behavior of these configurations with compaction and cleaning
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499483122
sounds good i am running same test on Glue now lets see if that works
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] phantomcoder62 commented on issue #8040: [SUPPORT] Getting error when writing into HUDI table if schema changed (datatype changed / column dropped)
Posted by "phantomcoder62 (via GitHub)" <gi...@apache.org>.
phantomcoder62 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1448007139
> MOR
We are running our production code for Hudi upsert on EC2. We are not using any job parameter for that. In AWS glue, we are using the configuration --datalake-formats having value 'hudi'
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1451832086
Good Morning
Can some one Please provide some updates regarding this tickets ?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499526827
Here is New Ticket https://github.com/apache/hudi/issues/8401 @voonhous
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] phantomcoder62 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "phantomcoder62 (via GitHub)" <gi...@apache.org>.
phantomcoder62 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1495521020
Hello HUDI Team,
Any update on the above issue? We have to go live in 2 weeks.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] voonhous commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "voonhous (via GitHub)" <gi...@apache.org>.
voonhous commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499487516
@soumilshah1995
Seems like a glue issue. I think it's better to open a new issue regarding the problem you are facing.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1449038756
I require additional information in order to test things on my end. Please let me know if you are using Kinesis to analyze streaming data.I would want to get an example dataset of some kind. if you can explain me which column were you trying to remove ?
Can you please tell me which Hudi version are you using (0.12 OR 0.13)?
What Spark version ?
Are you using via AWS glue connector ? if yes did you update to connector ?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1443831103
please share your job parameters
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497476139
they re job param
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497369964
> still doesn't work, is it p
The complete example is provided above; if you require more details, please let me know.
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1497489159
same issue
after adding conf you mentioned
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1499476749
> ie.schema.on.read.enable" -> "true",
> "hoodie.datasource.write.reconcile.schema" -> "true"
were you able to delete the column in glue ?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [hudi] soumilshah1995 commented on issue #8040: [SUPPORT] Getting error when writing into MOR HUDI table if schema changed (datatype changed / column dropped)
Posted by "soumilshah1995 (via GitHub)" <gi...@apache.org>.
soumilshah1995 commented on issue #8040:
URL: https://github.com/apache/hudi/issues/8040#issuecomment-1475435614
Any updates on this issue ?
--
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: commits-unsubscribe@hudi.apache.org
For queries about this service, please contact Infrastructure at:
users@infra.apache.org