menna224 opened a new issue, #7897:
URL: https://github.com/apache/hudi/issues/7897
I am having a glue job in which I write to hudi table, and I write it as MOR
here's the config:
conf = {
'className': 'org.apache.hudi',
'hoodie.table.name': hudi_table_name,
'hoodie.datasource.write.operation': 'upsert',
'hoodie.datasource.write.table.type': 'MERGE_ON_READ',
'hoodie.datasource.write.precombine.field': 'timestamp',
'hoodie.datasource.write.recordkey.field': 'user_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': 'DATE_STRING',
#'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': 'false',
#'hoodie.datasource.hive_sync.partition_extractor_class':
'org.apache.hudi.hive.MultiPartKeysValueExtractor',
#'hoodie.datasource.hive_sync.partition_fields': 'year,month,day'
}
config_={**conf, **hudiGlueConfig}
I noticed that for each new record I append I had parquet file, and when I
update any of them I have a log file contains the update, and after number of
appends the parqeut files compacted into one parquet file. However, this file
contains the old values of initially added records, not the updated ones, any
clue what I might be doing wrong?
the rt view reflects the correct data, the ro doesn't.
I am writing it as:
glueContext.forEachBatch( frame=data_frame_DataSource0,
batch_function=processBatch, options={ "windowSize": window_size,
"checkpointLocation": s3_path_spark } )
glueContext.write_dynamic_frame.from_options(
frame=DynamicFrame.fromDF(df, glueContext, "df"),
connection_type="custom.spark",
connection_options=config_
)
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