nsivabalan commented on issue #6194:
URL: https://github.com/apache/hudi/issues/6194#issuecomment-1210103983
these set of commands worked for me.
I followed our quick start guide, just by setting write operation to
"bulk_insert". I repeated the same insert Df twice to hudi table.
```
spark.sql("select partitionpath, count(uuid) from hudi_trips_snapshot group
by 1 order by 1").show(false)
+------------------------------------+-----------+
|partitionpath |count(uuid)|
+------------------------------------+-----------+
|americas/brazil/sao_paulo |6 |
|americas/united_states/san_francisco|10 |
|asia/india/chennai |4 |
+------------------------------------+-----------+
spark.sql("select partitionpath, uuid, fare from hudi_trips_snapshot order
by 1,2").show(false)
+------------------------------------+------------------------------------+------------------+
|partitionpath |uuid
|fare |
+------------------------------------+------------------------------------+------------------+
|americas/brazil/sao_paulo
|69f49197-cc8e-4d91-b745-dbe6e83a4b5a|66.62084366450246 |
|americas/brazil/sao_paulo
|69f49197-cc8e-4d91-b745-dbe6e83a4b5a|66.62084366450246 |
|americas/brazil/sao_paulo
|be747659-1a1d-4445-b5ae-ccfe5104e69e|43.4923811219014 |
|americas/brazil/sao_paulo
|be747659-1a1d-4445-b5ae-ccfe5104e69e|43.4923811219014 |
|americas/brazil/sao_paulo
|ebe7576f-18c6-4cb8-b119-94ac7bb518c2|34.158284716382845|
|americas/brazil/sao_paulo
|ebe7576f-18c6-4cb8-b119-94ac7bb518c2|34.158284716382845|
|americas/united_states/san_francisco|07ce908b-1f5e-405f-98fb-37796264d7c3|19.179139106643607|
|americas/united_states/san_francisco|07ce908b-1f5e-405f-98fb-37796264d7c3|19.179139106643607|
|americas/united_states/san_francisco|09e8d4d3-f6ce-425a-8b8a-1858d9aea981|64.27696295884016
|
|americas/united_states/san_francisco|09e8d4d3-f6ce-425a-8b8a-1858d9aea981|64.27696295884016
|
|americas/united_states/san_francisco|15b605fb-4ce7-4f37-a1ec-79989ae9b90f|33.92216483948643
|
|americas/united_states/san_francisco|15b605fb-4ce7-4f37-a1ec-79989ae9b90f|33.92216483948643
|
|americas/united_states/san_francisco|ac572297-8aa7-4cfc-be1b-280ab8b6c783|27.79478688582596
|
|americas/united_states/san_francisco|ac572297-8aa7-4cfc-be1b-280ab8b6c783|27.79478688582596
|
|americas/united_states/san_francisco|de8d8395-f3aa-412a-bb49-78f4e2537677|93.56018115236618
|
|americas/united_states/san_francisco|de8d8395-f3aa-412a-bb49-78f4e2537677|93.56018115236618
|
|asia/india/chennai
|047c2afe-3cb1-4976-badb-10042a33e9e9|41.06290929046368 |
|asia/india/chennai
|047c2afe-3cb1-4976-badb-10042a33e9e9|41.06290929046368 |
|asia/india/chennai
|f74ac5dc-a908-4669-b607-8a382ffbf103|17.851135255091155|
|asia/india/chennai
|f74ac5dc-a908-4669-b607-8a382ffbf103|17.851135255091155|
+------------------------------------+------------------------------------+------------------+
```
de-dup via hudi-cli
```
Launch hudi-cli
connect --path /tmp/hudi_trips_cow/
set --conf SPARK_HOME=/Users/nsb/Documents/tools/spark-2.4.7-bin-hadoop2.7
repair deduplicate --duplicatedPartitionPath "americas/brazil/sao_paulo"
--repairedOutputPath "/tmp/dedupedData/" --sparkMemory 1g --sparkMaster
local[2] --dedupeType "upsert_type"
```
After this, I see some parquet files in "/tmp/dedupedData/". I tried reading
them via spark-shell to check for duplicates.
```
val df = spark.read.format("parquet").load("/tmp/dedupedData/")
df.registerTempTable("tbl1")
spark.sql("select partitionpath, uuid, fare from tbl1 order by
1,2").show(false)
+-------------------------+------------------------------------+------------------+
|partitionpath |uuid |fare
|
+-------------------------+------------------------------------+------------------+
|americas/brazil/sao_paulo|69f49197-cc8e-4d91-b745-dbe6e83a4b5a|66.62084366450246
|
|americas/brazil/sao_paulo|be747659-1a1d-4445-b5ae-ccfe5104e69e|43.4923811219014
|
|americas/brazil/sao_paulo|ebe7576f-18c6-4cb8-b119-94ac7bb518c2|34.158284716382845|
+-------------------------+------------------------------------+------------------+
```
Let me know if this helps.
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