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Posted to commits@hudi.apache.org by GitBox <gi...@apache.org> on 2022/09/14 15:06:56 UTC

[GitHub] [hudi] jonvex opened a new pull request, #6672: [HUDI-4757] Create pyspark examples

jonvex opened a new pull request, #6672:
URL: https://github.com/apache/hudi/pull/6672

   ### Change Logs
   
   Create examples in pyspark and add validations to them
   
   ### Impact
   
   Can be used for new users. Might be used for CI testing
   
   **Risk level: low **
   
   _Choose one. If medium or high, explain what verification was done to mitigate the risks._
   
   ### Contributor's checklist
   
   - [ ] Read through [contributor's guide](https://hudi.apache.org/contribute/how-to-contribute)
   - [ ] Change Logs and Impact were stated clearly
   - [ ] Adequate tests were added if applicable
   - [ ] CI passed
   


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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1247480503

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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1249595330

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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1247369500

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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1246925549

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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1246917198

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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1247090049

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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1250112195

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[GitHub] [hudi] yihua merged pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
yihua merged PR #6672:
URL: https://github.com/apache/hudi/pull/6672


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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1249590783

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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1250111224

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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1250003354

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[GitHub] [hudi] nsivabalan commented on a diff in pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
nsivabalan commented on code in PR #6672:
URL: https://github.com/apache/hudi/pull/6672#discussion_r972359680


##########
hudi-spark-datasource/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java:
##########
@@ -190,6 +192,30 @@ public List<HoodieRecord> generateUpdates(Integer n) {
       }).collect(Collectors.toList());
     }
 
+    /**
+     * Generates new updates, one for each of the keys above
+     * list
+     *
+     * @param n Number of updates (must be no more than number of existing keys)
+     * @return list of hoodie record updates
+     */
+    public List<HoodieRecord> generateUniqueUpdatesForExample(Integer n) {

Review Comment:
   what "example" matters? why can't we make it generic to be used even in our tests? 



##########
hudi-spark-datasource/hudi-spark/src/main/java/org/apache/hudi/QuickstartUtils.java:
##########
@@ -190,6 +192,30 @@ public List<HoodieRecord> generateUpdates(Integer n) {
       }).collect(Collectors.toList());
     }
 
+    /**
+     * Generates new updates, one for each of the keys above
+     * list
+     *
+     * @param n Number of updates (must be no more than number of existing keys)
+     * @return list of hoodie record updates
+     */
+    public List<HoodieRecord> generateUniqueUpdatesForExample(Integer n) {

Review Comment:
   oh, this datagenerator is used just for QuickStartUtils. so, you can just name this "generateUniqueUpdates". would suffice.



##########
hudi-examples/hudi-examples-spark/src/test/python/HoodiePySparkQuickstart.py:
##########
@@ -0,0 +1,260 @@
+#   Licensed to the Apache Software Foundation (ASF) under one
+#   or more contributor license agreements.  See the NOTICE file
+#   distributed with this work for additional information
+#   regarding copyright ownership.  The ASF licenses this file
+#   to you under the Apache License, Version 2.0 (the
+#   "License"); you may not use this file except in compliance
+#   with the License.  You may obtain a copy of the License at
+ 
+#       http://www.apache.org/licenses/LICENSE-2.0
+ 
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+ 
+
+import sys
+import os
+from pyspark import sql
+import random
+from pyspark.sql.functions import lit
+from functools import reduce
+import tempfile
+
+
+
+class ExamplePySpark:
+    def __init__(self, spark: sql.SparkSession, tableName: str, basePath: str):
+        self.spark = spark
+        self.tableName = tableName
+        self.basePath = basePath + "/" + tableName
+        self.hudi_options = {
+            'hoodie.table.name': tableName,
+            'hoodie.datasource.write.recordkey.field': 'uuid',
+            'hoodie.datasource.write.partitionpath.field': 'partitionpath',
+            'hoodie.datasource.write.table.name': tableName,
+            'hoodie.datasource.write.operation': 'upsert',
+            'hoodie.datasource.write.precombine.field': 'ts',
+            'hoodie.upsert.shuffle.parallelism': 2,
+            'hoodie.insert.shuffle.parallelism': 2
+        }
+
+        self.dataGen = spark._jvm.org.apache.hudi.QuickstartUtils.DataGenerator()
+        self.snapshotQuery = "SELECT begin_lat, begin_lon, driver, end_lat, end_lon, fare, partitionpath, rider, ts, uuid FROM hudi_trips_snapshot"
+        return
+
+    def runQuickstart(self):
+        
+        def snap():
+            return self.spark.sql(self.snapshotQuery)
+        insertDf = self.insertData()
+        self.queryData()
+        assert len(insertDf.exceptAll(snap()).collect()) == 0
+        
+        snapshotBeforeUpdate = snap()
+        updateDf = self.updateData()
+        self.queryData()
+        assert len(snap().intersect(updateDf).collect()) == len(updateDf.collect())
+        assert len(snap().exceptAll(updateDf).exceptAll(snapshotBeforeUpdate).collect()) == 0
+
+
+        self.timeTravelQuery()
+        self.incrementalQuery()
+        self.pointInTimeQuery()
+
+        self.softDeletes()
+        self.queryData()
+
+        snapshotBeforeDelete = snap()
+        deletesDf = self.hardDeletes()
+        self.queryData()
+        assert len(snap().select(["uuid", "partitionpath", "ts"]).intersect(deletesDf).collect()) == 0
+        assert len(snapshotBeforeDelete.exceptAll(snap()).exceptAll(snapshotBeforeDelete).collect()) == 0
+
+        snapshotBeforeInsertOverwrite = snap()    
+        insertOverwriteDf = self.insertOverwrite()
+        self.queryData()
+        withoutSanFran = snapshotBeforeInsertOverwrite.filter("partitionpath != 'americas/united_states/san_francisco'")
+        expectedDf = withoutSanFran.union(insertOverwriteDf)
+        assert len(snap().exceptAll(expectedDf).collect()) == 0
+        return
+
+    def insertData(self):
+        print("Insert Data")
+        inserts = self.spark._jvm.org.apache.hudi.QuickstartUtils.convertToStringList(self.dataGen.generateInserts(10))
+        df = self.spark.read.json(self.spark.sparkContext.parallelize(inserts, 2))
+        df.write.format("hudi").options(**self.hudi_options).mode("overwrite").save(self.basePath)
+        return df
+
+    def updateData(self):
+        print("Update Data")
+        updates = self.spark._jvm.org.apache.hudi.QuickstartUtils.convertToStringList(self.dataGen.generateUniqueUpdatesForExample(5))
+        df = self.spark.read.json(spark.sparkContext.parallelize(updates, 2))
+        df.write.format("hudi").options(**self.hudi_options).mode("append").save(self.basePath)
+        return df
+
+    def queryData(self):
+        print("Query Data")
+        tripsSnapshotDF = self.spark.read.format("hudi").load(self.basePath)
+        tripsSnapshotDF.createOrReplaceTempView("hudi_trips_snapshot")
+        self.spark.sql("SELECT fare, begin_lon, begin_lat, ts FROM  hudi_trips_snapshot WHERE fare > 20.0").show()
+        self.spark.sql("SELECT _hoodie_commit_time, _hoodie_record_key, _hoodie_partition_path, rider, driver, fare FROM  hudi_trips_snapshot").show()
+        return
+
+    def timeTravelQuery(self):
+        query = "SELECT begin_lat, begin_lon, driver, end_lat, end_lon, fare, partitionpath, rider, ts, uuid FROM time_travel_query"
+        print("Time Travel Query")
+        self.spark.read.format("hudi").option("as.of.instant", "20210728141108").load(self.basePath).createOrReplaceTempView("time_travel_query")
+        self.spark.sql(query)
+        self.spark.read.format("hudi").option("as.of.instant", "2021-07-28 14:11:08.000").load(self.basePath).createOrReplaceTempView("time_travel_query")
+        self.spark.sql(query)
+        self.spark.read.format("hudi").option("as.of.instant", "2021-07-28").load(self.basePath).createOrReplaceTempView("time_travel_query")
+        self.spark.sql(query)
+        return
+    
+    def incrementalQuery(self):
+        print("Incremental Query")
+        self.spark.read.format("hudi").load(self.basePath).createOrReplaceTempView("hudi_trips_snapshot")
+        self.commits = list(map(lambda row: row[0], self.spark.sql("SELECT DISTINCT(_hoodie_commit_time) AS commitTime FROM  hudi_trips_snapshot ORDER BY commitTime").limit(50).collect()))
+        beginTime = self.commits[len(self.commits) - 2] 
+        incremental_read_options = {
+            'hoodie.datasource.query.type': 'incremental',
+            'hoodie.datasource.read.begin.instanttime': beginTime,
+        }
+        tripsIncrementalDF = self.spark.read.format("hudi").options(**incremental_read_options).load(self.basePath)
+        tripsIncrementalDF.createOrReplaceTempView("hudi_trips_incremental")
+        self.spark.sql("SELECT `_hoodie_commit_time`, fare, begin_lon, begin_lat, ts FROM hudi_trips_incremental WHERE fare > 20.0").show()
+
+    def pointInTimeQuery(self):
+        print("Point-in-time Query")
+        beginTime = "000"
+        endTime = self.commits[len(self.commits) - 2]
+        point_in_time_read_options = {
+            'hoodie.datasource.query.type': 'incremental',
+            'hoodie.datasource.read.end.instanttime': endTime,
+            'hoodie.datasource.read.begin.instanttime': beginTime
+        }
+
+        tripsPointInTimeDF = self.spark.read.format("hudi").options(**point_in_time_read_options).load(self.basePath)
+        tripsPointInTimeDF.createOrReplaceTempView("hudi_trips_point_in_time")
+        self.spark.sql("SELECT `_hoodie_commit_time`, fare, begin_lon, begin_lat, ts FROM hudi_trips_point_in_time WHERE fare > 20.0").show()
+    
+    def softDeletes(self):
+        print("Soft Deletes")
+        spark.read.format("hudi").load(self.basePath).createOrReplaceTempView("hudi_trips_snapshot")
+
+        # fetch total records count
+        trip_count = spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").count()
+        non_null_rider_count = spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot WHERE rider IS NOT null").count()
+        print(f"trip count: {trip_count}, non null rider count: {non_null_rider_count}")
+        # fetch two records for soft deletes
+        soft_delete_ds = spark.sql("SELECT * FROM hudi_trips_snapshot").limit(2)
+        # prepare the soft deletes by ensuring the appropriate fields are nullified
+        meta_columns = ["_hoodie_commit_time", "_hoodie_commit_seqno", "_hoodie_record_key", 
+        "_hoodie_partition_path", "_hoodie_file_name"]
+        excluded_columns = meta_columns + ["ts", "uuid", "partitionpath"]
+        nullify_columns = list(filter(lambda field: field[0] not in excluded_columns, \
+        list(map(lambda field: (field.name, field.dataType), soft_delete_ds.schema.fields))))
+
+        hudi_soft_delete_options = {
+        'hoodie.table.name': self.tableName,
+        'hoodie.datasource.write.recordkey.field': 'uuid',
+        'hoodie.datasource.write.partitionpath.field': 'partitionpath',
+        'hoodie.datasource.write.table.name': self.tableName,
+        'hoodie.datasource.write.operation': 'upsert',
+        'hoodie.datasource.write.precombine.field': 'ts',
+        'hoodie.upsert.shuffle.parallelism': 2, 
+        'hoodie.insert.shuffle.parallelism': 2
+        }
+
+        soft_delete_df = reduce(lambda df,col: df.withColumn(col[0], lit(None).cast(col[1])), \
+        nullify_columns, reduce(lambda df,col: df.drop(col[0]), meta_columns, soft_delete_ds))
+
+        # simply upsert the table after setting these fields to null
+        soft_delete_df.write.format("hudi").options(**hudi_soft_delete_options).mode("append").save(self.basePath)
+
+        # reload data
+        self.spark.read.format("hudi").load(self.basePath).createOrReplaceTempView("hudi_trips_snapshot")
+
+        # This should return the same total count as before
+        trip_count = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").count()
+        # This should return (total - 2) count as two records are updated with nulls
+        non_null_rider_count = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot WHERE rider IS NOT null").count()
+        print(f"trip count: {trip_count}, non null rider count: {non_null_rider_count}")
+
+    def hardDeletes(self):
+        print("Hard Deletes")
+        # fetch total records count
+        total_count = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").count()
+        print(f"total count: {total_count}")
+        # fetch two records to be deleted
+        ds = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").limit(2)
+
+        # issue deletes
+        hudi_hard_delete_options = {
+            'hoodie.table.name': self.tableName,
+            'hoodie.datasource.write.recordkey.field': 'uuid',
+            'hoodie.datasource.write.partitionpath.field': 'partitionpath',
+            'hoodie.datasource.write.table.name': self.tableName,
+            'hoodie.datasource.write.operation': 'delete',
+            'hoodie.datasource.write.precombine.field': 'ts',
+            'hoodie.upsert.shuffle.parallelism': 2, 
+            'hoodie.insert.shuffle.parallelism': 2
+        }
+
+        deletes = list(map(lambda row: (row[0], row[1]), ds.collect()))
+        hard_delete_df = self.spark.sparkContext.parallelize(deletes).toDF(['uuid', 'partitionpath']).withColumn('ts', lit(0.0))
+        hard_delete_df.write.format("hudi").options(**hudi_hard_delete_options).mode("append").save(self.basePath)
+
+        # run the same read query as above.
+        roAfterDeleteViewDF = self.spark.read.format("hudi").load(self.basePath) 
+        roAfterDeleteViewDF.createOrReplaceTempView("hudi_trips_snapshot")
+        # fetch should return (total - 2) records
+        total_count = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").count()
+        print(f"total count: {total_count}")
+        return hard_delete_df
+
+    def insertOverwrite(self):
+        print("Insert Overwrite")
+        self.spark.read.format("hudi").load(self.basePath).select(["uuid","partitionpath"]).sort(["partitionpath", "uuid"]).show(n=100,truncate=False)
+        inserts = self.spark._jvm.org.apache.hudi.QuickstartUtils.convertToStringList(self.dataGen.generateInserts(10))
+        df = self.spark.read.json(self.spark.sparkContext.parallelize(inserts, 2)).filter("partitionpath = 'americas/united_states/san_francisco'")
+        hudi_insert_overwrite_options = {
+            'hoodie.table.name': self.tableName,
+            'hoodie.datasource.write.recordkey.field': 'uuid',
+            'hoodie.datasource.write.partitionpath.field': 'partitionpath',
+            'hoodie.datasource.write.table.name': self.tableName,
+            'hoodie.datasource.write.operation': 'insert_overwrite',
+            'hoodie.datasource.write.precombine.field': 'ts',
+            'hoodie.upsert.shuffle.parallelism': 2,
+            'hoodie.insert.shuffle.parallelism': 2
+        }
+        df.write.format("hudi").options(**hudi_insert_overwrite_options).mode("append").save(self.basePath)
+        self.spark.read.format("hudi").load(self.basePath).select(["uuid","partitionpath"]).sort(["partitionpath", "uuid"]).show(n=100,truncate=False)
+        return df
+
+if __name__ == "__main__":
+    random.seed(46474747)
+    if len(sys.argv) < 3:
+        print("Usage: python3 HoodiePySparkQuickstart.py <tableName> <jar file path/bundle name>")

Review Comment:
   while testing you tested using local jar. but we want to test it w/ `--packages` as well. can we take an argument and add `--packages` or `--jars` based on that. 
   



##########
hudi-examples/hudi-examples-spark/src/test/python/HoodiePySparkQuickstart.py:
##########
@@ -0,0 +1,260 @@
+#   Licensed to the Apache Software Foundation (ASF) under one
+#   or more contributor license agreements.  See the NOTICE file
+#   distributed with this work for additional information
+#   regarding copyright ownership.  The ASF licenses this file
+#   to you under the Apache License, Version 2.0 (the
+#   "License"); you may not use this file except in compliance
+#   with the License.  You may obtain a copy of the License at
+ 
+#       http://www.apache.org/licenses/LICENSE-2.0
+ 
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+ 
+
+import sys
+import os
+from pyspark import sql
+import random
+from pyspark.sql.functions import lit
+from functools import reduce
+import tempfile
+
+
+
+class ExamplePySpark:
+    def __init__(self, spark: sql.SparkSession, tableName: str, basePath: str):
+        self.spark = spark
+        self.tableName = tableName
+        self.basePath = basePath + "/" + tableName
+        self.hudi_options = {
+            'hoodie.table.name': tableName,
+            'hoodie.datasource.write.recordkey.field': 'uuid',
+            'hoodie.datasource.write.partitionpath.field': 'partitionpath',
+            'hoodie.datasource.write.table.name': tableName,
+            'hoodie.datasource.write.operation': 'upsert',
+            'hoodie.datasource.write.precombine.field': 'ts',
+            'hoodie.upsert.shuffle.parallelism': 2,
+            'hoodie.insert.shuffle.parallelism': 2
+        }
+
+        self.dataGen = spark._jvm.org.apache.hudi.QuickstartUtils.DataGenerator()
+        self.snapshotQuery = "SELECT begin_lat, begin_lon, driver, end_lat, end_lon, fare, partitionpath, rider, ts, uuid FROM hudi_trips_snapshot"
+        return
+
+    def runQuickstart(self):
+        
+        def snap():
+            return self.spark.sql(self.snapshotQuery)
+        insertDf = self.insertData()
+        self.queryData()
+        assert len(insertDf.exceptAll(snap()).collect()) == 0
+        
+        snapshotBeforeUpdate = snap()
+        updateDf = self.updateData()
+        self.queryData()
+        assert len(snap().intersect(updateDf).collect()) == len(updateDf.collect())
+        assert len(snap().exceptAll(updateDf).exceptAll(snapshotBeforeUpdate).collect()) == 0
+
+
+        self.timeTravelQuery()
+        self.incrementalQuery()
+        self.pointInTimeQuery()
+
+        self.softDeletes()
+        self.queryData()
+
+        snapshotBeforeDelete = snap()
+        deletesDf = self.hardDeletes()
+        self.queryData()
+        assert len(snap().select(["uuid", "partitionpath", "ts"]).intersect(deletesDf).collect()) == 0
+        assert len(snapshotBeforeDelete.exceptAll(snap()).exceptAll(snapshotBeforeDelete).collect()) == 0
+
+        snapshotBeforeInsertOverwrite = snap()    
+        insertOverwriteDf = self.insertOverwrite()
+        self.queryData()
+        withoutSanFran = snapshotBeforeInsertOverwrite.filter("partitionpath != 'americas/united_states/san_francisco'")
+        expectedDf = withoutSanFran.union(insertOverwriteDf)
+        assert len(snap().exceptAll(expectedDf).collect()) == 0
+        return
+
+    def insertData(self):
+        print("Insert Data")
+        inserts = self.spark._jvm.org.apache.hudi.QuickstartUtils.convertToStringList(self.dataGen.generateInserts(10))
+        df = self.spark.read.json(self.spark.sparkContext.parallelize(inserts, 2))
+        df.write.format("hudi").options(**self.hudi_options).mode("overwrite").save(self.basePath)
+        return df
+
+    def updateData(self):
+        print("Update Data")
+        updates = self.spark._jvm.org.apache.hudi.QuickstartUtils.convertToStringList(self.dataGen.generateUniqueUpdatesForExample(5))
+        df = self.spark.read.json(spark.sparkContext.parallelize(updates, 2))
+        df.write.format("hudi").options(**self.hudi_options).mode("append").save(self.basePath)
+        return df
+
+    def queryData(self):
+        print("Query Data")
+        tripsSnapshotDF = self.spark.read.format("hudi").load(self.basePath)
+        tripsSnapshotDF.createOrReplaceTempView("hudi_trips_snapshot")
+        self.spark.sql("SELECT fare, begin_lon, begin_lat, ts FROM  hudi_trips_snapshot WHERE fare > 20.0").show()
+        self.spark.sql("SELECT _hoodie_commit_time, _hoodie_record_key, _hoodie_partition_path, rider, driver, fare FROM  hudi_trips_snapshot").show()
+        return
+
+    def timeTravelQuery(self):
+        query = "SELECT begin_lat, begin_lon, driver, end_lat, end_lon, fare, partitionpath, rider, ts, uuid FROM time_travel_query"
+        print("Time Travel Query")
+        self.spark.read.format("hudi").option("as.of.instant", "20210728141108").load(self.basePath).createOrReplaceTempView("time_travel_query")
+        self.spark.sql(query)
+        self.spark.read.format("hudi").option("as.of.instant", "2021-07-28 14:11:08.000").load(self.basePath).createOrReplaceTempView("time_travel_query")
+        self.spark.sql(query)
+        self.spark.read.format("hudi").option("as.of.instant", "2021-07-28").load(self.basePath).createOrReplaceTempView("time_travel_query")
+        self.spark.sql(query)
+        return
+    
+    def incrementalQuery(self):
+        print("Incremental Query")
+        self.spark.read.format("hudi").load(self.basePath).createOrReplaceTempView("hudi_trips_snapshot")
+        self.commits = list(map(lambda row: row[0], self.spark.sql("SELECT DISTINCT(_hoodie_commit_time) AS commitTime FROM  hudi_trips_snapshot ORDER BY commitTime").limit(50).collect()))
+        beginTime = self.commits[len(self.commits) - 2] 
+        incremental_read_options = {
+            'hoodie.datasource.query.type': 'incremental',
+            'hoodie.datasource.read.begin.instanttime': beginTime,
+        }
+        tripsIncrementalDF = self.spark.read.format("hudi").options(**incremental_read_options).load(self.basePath)
+        tripsIncrementalDF.createOrReplaceTempView("hudi_trips_incremental")
+        self.spark.sql("SELECT `_hoodie_commit_time`, fare, begin_lon, begin_lat, ts FROM hudi_trips_incremental WHERE fare > 20.0").show()
+
+    def pointInTimeQuery(self):
+        print("Point-in-time Query")
+        beginTime = "000"
+        endTime = self.commits[len(self.commits) - 2]
+        point_in_time_read_options = {
+            'hoodie.datasource.query.type': 'incremental',
+            'hoodie.datasource.read.end.instanttime': endTime,
+            'hoodie.datasource.read.begin.instanttime': beginTime
+        }
+
+        tripsPointInTimeDF = self.spark.read.format("hudi").options(**point_in_time_read_options).load(self.basePath)
+        tripsPointInTimeDF.createOrReplaceTempView("hudi_trips_point_in_time")
+        self.spark.sql("SELECT `_hoodie_commit_time`, fare, begin_lon, begin_lat, ts FROM hudi_trips_point_in_time WHERE fare > 20.0").show()
+    
+    def softDeletes(self):
+        print("Soft Deletes")
+        spark.read.format("hudi").load(self.basePath).createOrReplaceTempView("hudi_trips_snapshot")
+
+        # fetch total records count
+        trip_count = spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").count()
+        non_null_rider_count = spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot WHERE rider IS NOT null").count()
+        print(f"trip count: {trip_count}, non null rider count: {non_null_rider_count}")
+        # fetch two records for soft deletes
+        soft_delete_ds = spark.sql("SELECT * FROM hudi_trips_snapshot").limit(2)
+        # prepare the soft deletes by ensuring the appropriate fields are nullified
+        meta_columns = ["_hoodie_commit_time", "_hoodie_commit_seqno", "_hoodie_record_key", 
+        "_hoodie_partition_path", "_hoodie_file_name"]
+        excluded_columns = meta_columns + ["ts", "uuid", "partitionpath"]
+        nullify_columns = list(filter(lambda field: field[0] not in excluded_columns, \
+        list(map(lambda field: (field.name, field.dataType), soft_delete_ds.schema.fields))))
+
+        hudi_soft_delete_options = {
+        'hoodie.table.name': self.tableName,
+        'hoodie.datasource.write.recordkey.field': 'uuid',
+        'hoodie.datasource.write.partitionpath.field': 'partitionpath',
+        'hoodie.datasource.write.table.name': self.tableName,
+        'hoodie.datasource.write.operation': 'upsert',
+        'hoodie.datasource.write.precombine.field': 'ts',
+        'hoodie.upsert.shuffle.parallelism': 2, 
+        'hoodie.insert.shuffle.parallelism': 2
+        }
+
+        soft_delete_df = reduce(lambda df,col: df.withColumn(col[0], lit(None).cast(col[1])), \
+        nullify_columns, reduce(lambda df,col: df.drop(col[0]), meta_columns, soft_delete_ds))
+
+        # simply upsert the table after setting these fields to null
+        soft_delete_df.write.format("hudi").options(**hudi_soft_delete_options).mode("append").save(self.basePath)
+
+        # reload data
+        self.spark.read.format("hudi").load(self.basePath).createOrReplaceTempView("hudi_trips_snapshot")
+
+        # This should return the same total count as before
+        trip_count = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").count()
+        # This should return (total - 2) count as two records are updated with nulls
+        non_null_rider_count = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot WHERE rider IS NOT null").count()
+        print(f"trip count: {trip_count}, non null rider count: {non_null_rider_count}")
+
+    def hardDeletes(self):
+        print("Hard Deletes")
+        # fetch total records count
+        total_count = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").count()
+        print(f"total count: {total_count}")
+        # fetch two records to be deleted
+        ds = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").limit(2)
+
+        # issue deletes
+        hudi_hard_delete_options = {
+            'hoodie.table.name': self.tableName,
+            'hoodie.datasource.write.recordkey.field': 'uuid',
+            'hoodie.datasource.write.partitionpath.field': 'partitionpath',
+            'hoodie.datasource.write.table.name': self.tableName,
+            'hoodie.datasource.write.operation': 'delete',
+            'hoodie.datasource.write.precombine.field': 'ts',
+            'hoodie.upsert.shuffle.parallelism': 2, 
+            'hoodie.insert.shuffle.parallelism': 2
+        }
+
+        deletes = list(map(lambda row: (row[0], row[1]), ds.collect()))
+        hard_delete_df = self.spark.sparkContext.parallelize(deletes).toDF(['uuid', 'partitionpath']).withColumn('ts', lit(0.0))
+        hard_delete_df.write.format("hudi").options(**hudi_hard_delete_options).mode("append").save(self.basePath)
+
+        # run the same read query as above.
+        roAfterDeleteViewDF = self.spark.read.format("hudi").load(self.basePath) 
+        roAfterDeleteViewDF.createOrReplaceTempView("hudi_trips_snapshot")
+        # fetch should return (total - 2) records
+        total_count = self.spark.sql("SELECT uuid, partitionpath FROM hudi_trips_snapshot").count()
+        print(f"total count: {total_count}")
+        return hard_delete_df
+
+    def insertOverwrite(self):
+        print("Insert Overwrite")
+        self.spark.read.format("hudi").load(self.basePath).select(["uuid","partitionpath"]).sort(["partitionpath", "uuid"]).show(n=100,truncate=False)
+        inserts = self.spark._jvm.org.apache.hudi.QuickstartUtils.convertToStringList(self.dataGen.generateInserts(10))
+        df = self.spark.read.json(self.spark.sparkContext.parallelize(inserts, 2)).filter("partitionpath = 'americas/united_states/san_francisco'")
+        hudi_insert_overwrite_options = {
+            'hoodie.table.name': self.tableName,
+            'hoodie.datasource.write.recordkey.field': 'uuid',
+            'hoodie.datasource.write.partitionpath.field': 'partitionpath',
+            'hoodie.datasource.write.table.name': self.tableName,
+            'hoodie.datasource.write.operation': 'insert_overwrite',
+            'hoodie.datasource.write.precombine.field': 'ts',
+            'hoodie.upsert.shuffle.parallelism': 2,
+            'hoodie.insert.shuffle.parallelism': 2
+        }
+        df.write.format("hudi").options(**hudi_insert_overwrite_options).mode("append").save(self.basePath)
+        self.spark.read.format("hudi").load(self.basePath).select(["uuid","partitionpath"]).sort(["partitionpath", "uuid"]).show(n=100,truncate=False)
+        return df
+
+if __name__ == "__main__":
+    random.seed(46474747)
+    if len(sys.argv) < 3:
+        print("Usage: python3 HoodiePySparkQuickstart.py <tableName> <jar file path/bundle name>")
+        quit(-1)
+    #Example jar filepath: /Users/jon/.m2/repository/org/apache/hudi/hudi-spark3.3-bundle_2.12/0.13.0-SNAPSHOT/hudi-spark3.3-bundle_2.12-0.13.0-SNAPSHOT.jar

Review Comment:
   Example jar path: [HUDI_BASE_PATH]/packaging/hudi-spark-bundle/target/hudi-spark-bundle[VERSION].jar 
   do not add any absolute paths in general. 



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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1247096030

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[GitHub] [hudi] yihua commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
yihua commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1250130056

   Comments are all addressed and CI passes.  I'll land this PR.  @nsivabalan feel free to follow up if needed.


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[GitHub] [hudi] hudi-bot commented on pull request #6672: [HUDI-4757] Create pyspark examples

Posted by GitBox <gi...@apache.org>.
hudi-bot commented on PR #6672:
URL: https://github.com/apache/hudi/pull/6672#issuecomment-1249600106

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