FredMkl opened a new issue, #6591:
URL: https://github.com/apache/hudi/issues/6591
**Describe the problem you faced**
We use MOR table, we found that when updating an existing set of rows to
another partition will result in both a)generate a parquet file b)an update
written to a log file. This brings duplicate records
**To Reproduce**
```
//action1: spark-dataframe write
import org.apache.spark.sql.SaveMode._
import org.apache.hudi.DataSourceReadOptions._
import org.apache.hudi.DataSourceWriteOptions._
import org.apache.spark.sql.{DataFrame, Row, SparkSession}
import scala.collection.mutable
val tableName = "f_schedule_test"
val basePath = "oss://nbadatalake-poc/fred/warehouse/dw/f_schedule_test"
val spark = SparkSession.builder.enableHiveSupport.getOrCreate
import spark.implicits._
// spark-shell
val df = Seq(
("1", "10001", "2022-08-30","2022-08-30 12:00:00.000","2022-08-30"),
("2", "10002", "2022-08-31","2022-08-30 12:00:00.000","2022-08-30"),
("3", "10003", "2022-08-31","2022-08-30 12:00:00.000","2022-08-30"),
("4", "10004", "2022-08-31","2022-08-30 12:00:00.000","2022-08-30"),
("5", "10005", "2022-08-31","2022-08-30 12:00:00.000","2022-08-30"),
("6", "10006", "2022-08-31","2022-08-30 12:00:00.000","2022-08-30")
).toDF("game_schedule_id", "game_id", "game_date_cn", "insert_date",
"dt")
// df.show()
val hudiOptions = mutable.Map(
"hoodie.datasource.write.table.type" -> "MERGE_ON_READ",
"hoodie.datasource.write.operation" -> "upsert",
"hoodie.datasource.write.recordkey.field" -> "game_schedule_id",
"hoodie.datasource.write.precombine.field" -> "insert_date",
"hoodie.datasource.write.partitionpath.field" -> "dt",
"hoodie.index.type" -> "GLOBAL_BLOOM",
"hoodie.compact.inline" -> "true",
"hoodie.datasource.write.keygenerator.class" ->
"org.apache.hudi.keygen.ComplexKeyGenerator"
)
//step1: insert --no issue
df.write.format("hudi").
options(hudiOptions).
mode(Append).
save(basePath)
//step2: move part data to another partition --no issue
val df1 = spark.sql("select * from dw.f_schedule_test where dt =
'2022-08-30'").withColumn("dt",lit("2022-08-31")).limit(3)
df1.write.format("hudi").
options(hudiOptions).
mode(Append).
save(basePath)
//step3: move back --duplicate occurs
//Updating an existing set of rows will result in either a) a companion
log/delta file for an existing base parquet file generated from a previous
compaction or b) an update written to a log/delta file in case no compaction
ever happened for it.
val df2 = spark.sql("select * from dw.f_schedule_test where dt =
'2022-08-31'").withColumn("dt",lit("2022-08-30")).limit(3)
df2.write.format("hudi").
options(hudiOptions).
mode(Append).
save(basePath)
```
**Checking scripts:**
```
select * from dw.f_schedule_test where game_schedule_id = 1;
select _hoodie_file_name,count(*) as co from dw.f_schedule_test group by
_hoodie_file_name;
```
**results:**
**Expected behavior**
Duplicate records should not occur
**Environment Description**
* Hudi version :0.10.1
* Spark version :3.2.1
* Hive version :3.1.2
* Hadoop version :3.2.1
* Storage (HDFS/S3/GCS..) :OSS
* Running on Docker? (yes/no) :no
[hoodie.zip](https://github.com/apache/hudi/files/9487065/hoodie.zip)
**Stacktrace**
```Pls check logs as attached
[hoodie.zip](https://github.com/apache/hudi/files/9487078/hoodie.zip)
```
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