lamber-ken commented on issue #1105: [WIP] [HUDI-405] Fix sync no hive partition at first time URL: https://github.com/apache/incubator-hudi/pull/1105#issuecomment-569981982 > > So, modify assumeDatePartitioning to ! assumeDatePartitioning is the best way to fix this issue. > > This is not going to fix this issue.. and we should not be changing this code.. It will cause side effects, like I mentioned before. > > Can we reproduce this issue in a unit test or sample code first? hi, follow bellow steps can reproduce this issuse 1, Define the PartitionValueExtractor ``` package org.apache.hudi.hive; import org.joda.time.DateTime; import org.joda.time.format.DateTimeFormat; import org.joda.time.format.DateTimeFormatter; import java.util.Collections; import java.util.List; public class DayPartitionValueExtractor implements PartitionValueExtractor { private transient DateTimeFormatter dtfOut; public DayPartitionValueExtractor() { this.dtfOut = DateTimeFormat.forPattern("yyyy-MM-dd"); } private DateTimeFormatter getDtfOut() { if (dtfOut == null) { dtfOut = DateTimeFormat.forPattern("yyyy-MM-dd"); } return dtfOut; } @Override public List<String> extractPartitionValuesInPath(String partitionPath) { String[] splits = partitionPath.split("-"); if (splits.length != 3) { throw new IllegalArgumentException( "Partition path " + partitionPath + " is not in the form yyyy-mm-dd "); } int year = Integer.parseInt(splits[0]); int mm = Integer.parseInt(splits[1]); int dd = Integer.parseInt(splits[2]); DateTime dateTime = new DateTime(year, mm, dd, 0, 0); return Collections.singletonList(getDtfOut().print(dateTime)); } } ``` 2, Write data by spark-shell ``` export SPARK_HOME=/work/BigData/install/spark/spark-2.3.3-bin-hadoop2.6 $${SPARK_HOME}/bin/spark-shell --packages org.apache.hudi:hudi-spark-bundle:0.5.0-incubating --conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer' import org.apache.spark.sql.SaveMode val basePath = "/tmp/hoodie_test" var datas = List("""{ "key": "uuid", "event_time": 1574297893836, "part_date": "2019-11-12"}""") val df = spark.read.json(spark.sparkContext.parallelize(datas, 2)) df.write.format("hudi"). option("hoodie.insert.shuffle.parallelism", "10"). option("hoodie.upsert.shuffle.parallelism", "10"). option("hoodie.delete.shuffle.parallelism", "10"). option("hoodie.bulkinsert.shuffle.parallelism", "10"). option("hoodie.datasource.hive_sync.enable", true). option("hoodie.datasource.hive_sync.jdbcurl", "jdbc:hive2://0.0.0.0:12326"). option("hoodie.datasource.hive_sync.username", "dcadmin"). option("hoodie.datasource.hive_sync.password", "dcadmin"). option("hoodie.datasource.hive_sync.database", "default"). option("hoodie.datasource.hive_sync.table", "hoodie_test"). option("hoodie.datasource.hive_sync.partition_fields", "part_date"). option("hoodie.datasource.hive_sync.assume_date_partitioning", true). option("hoodie.datasource.hive_sync.partition_extractor_class", "org.apache.hudi.hive.DayPartitionValueExtractor"). option("hoodie.datasource.write.precombine.field", "event_time"). option("hoodie.datasource.write.recordkey.field", "key"). option("hoodie.datasource.write.partitionpath.field", "part_date"). option("hoodie.table.name", "hoodie_test"). mode(SaveMode.Overwrite). save(basePath); ``` 3, Query data from hive ``` no data ```
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