ehurheap commented on issue #9807:
URL: https://github.com/apache/hudi/issues/9807#issuecomment-1745464144
Yes. I can write a dataframe to the same table, for example:
```
data.write
.format("org.apache.hudi.Spark32PlusDefaultSource")
.options(writeWithLocking)
.mode("append")
.save(tablePath)
```
where writeWithLocking options are:
```
(hoodie.bulkinsert.shuffle.parallelism,2)
(hoodie.bulkinsert.sort.mode,NONE)
(hoodie.clean.async,false)
(hoodie.clean.automatic,false)
(hoodie.cleaner.policy.failed.writes,LAZY)
(hoodie.combine.before.insert,false)
(hoodie.compact.inline,false)
(hoodie.compact.schedule.inline,false)
(hoodie.datasource.compaction.async.enable,false)
(hoodie.datasource.write.hive_style_partitioning,true)
(hoodie.datasource.write.keygenerator.class,org.apache.spark.sql.hudi.command.UuidKeyGenerator)
(hoodie.datasource.write.operation,bulk_insert)
(hoodie.datasource.write.partitionpath.field,env_id,week)
(hoodie.datasource.write.precombine.field,schematized_at)
(hoodie.datasource.write.recordkey.field,env_id,user_id)
(hoodie.datasource.write.row.writer.enable,false)
(hoodie.datasource.write.table.type,MERGE_ON_READ)
(hoodie.metadata.enable,false)
(hoodie.table.name,users_changes)
(hoodie.write.concurrency.mode,OPTIMISTIC_CONCURRENCY_CONTROL)
(hoodie.write.lock.dynamodb.endpoint_url,http://localhost:8000)
(hoodie.write.lock.dynamodb.partition_key,users_changes-us-east-1-local)
(hoodie.write.lock.dynamodb.region,us-east-1)
(hoodie.write.lock.dynamodb.table,datalake-locks)
(hoodie.write.lock.provider,org.apache.hudi.aws.transaction.lock.DynamoDBBasedLockProvider)
```
These locking configs are also in our production ingestion which writes to
hudi using spark structured streaming without error.
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