Pyspark spark.sql is slow when inserting single record to HIVE Orc table
Spark (standalone mode): 2.2.1 Hive: 2.2. All with default configuration.
Spark, Hive and Hadoop are on the same cluster, including 3 nodes (8G Mem, 8 2.1G cores).
We used rabbitMQ to receive the messages; in the MQ consumer, we transform the json messages to Dataframe (1 message is for 1 record), and use pyspark to insert the dataframe to HIVE Orc-formatted table by the following pyspark code:
df = self.spark.createDataFrame(df)
df.createOrReplaceTempView("tmp_table")
spark.sql("insert into table {} select * from tmp_table".format(table_name))
The spark.sql() function cost more than 3 seconds. And as the time goes by, it gets slower and can cost more than 10 seconds. We check the spark log, the sql job actually costs less than 1 second, usually 0.2 ~ 0.6 sec.
We try parquet before Orc, and also enlarge the executor memory from 1G to 2G. There is no great difference. The Hive table is not partitioned.
What might be the key issue?
python performance apache-spark hive
asked Nov 26 '18 at 9:56
passingerpassinger
75110
add a comment |
Spark (standalone mode): 2.2.1 Hive: 2.2. All with default configuration.
Spark, Hive and Hadoop are on the same cluster, including 3 nodes (8G Mem, 8 2.1G cores).
We used rabbitMQ to receive the messages; in the MQ consumer, we transform the json messages to Dataframe (1 message is for 1 record), and use pyspark to insert the dataframe to HIVE Orc-formatted table by the following pyspark code:
df = self.spark.createDataFrame(df)
df.createOrReplaceTempView("tmp_table")
spark.sql("insert into table {} select * from tmp_table".format(table_name))
The spark.sql() function cost more than 3 seconds. And as the time goes by, it gets slower and can cost more than 10 seconds. We check the spark log, the sql job actually costs less than 1 second, usually 0.2 ~ 0.6 sec.
We try parquet before Orc, and also enlarge the executor memory from 1G to 2G. There is no great difference. The Hive table is not partitioned.
What might be the key issue?
python performance apache-spark hive
asked Nov 26 '18 at 9:56
passingerpassinger
75110
add a comment |
Spark (standalone mode): 2.2.1 Hive: 2.2. All with default configuration.
Spark, Hive and Hadoop are on the same cluster, including 3 nodes (8G Mem, 8 2.1G cores).
We used rabbitMQ to receive the messages; in the MQ consumer, we transform the json messages to Dataframe (1 message is for 1 record), and use pyspark to insert the dataframe to HIVE Orc-formatted table by the following pyspark code:
df = self.spark.createDataFrame(df)
df.createOrReplaceTempView("tmp_table")
spark.sql("insert into table {} select * from tmp_table".format(table_name))
The spark.sql() function cost more than 3 seconds. And as the time goes by, it gets slower and can cost more than 10 seconds. We check the spark log, the sql job actually costs less than 1 second, usually 0.2 ~ 0.6 sec.
We try parquet before Orc, and also enlarge the executor memory from 1G to 2G. There is no great difference. The Hive table is not partitioned.
What might be the key issue?
python performance apache-spark hive
asked Nov 26 '18 at 9:56
passingerpassinger
75110
Spark (standalone mode): 2.2.1 Hive: 2.2. All with default configuration.
Spark, Hive and Hadoop are on the same cluster, including 3 nodes (8G Mem, 8 2.1G cores).
We used rabbitMQ to receive the messages; in the MQ consumer, we transform the json messages to Dataframe (1 message is for 1 record), and use pyspark to insert the dataframe to HIVE Orc-formatted table by the following pyspark code:
df = self.spark.createDataFrame(df)
df.createOrReplaceTempView("tmp_table")
spark.sql("insert into table {} select * from tmp_table".format(table_name))
The spark.sql() function cost more than 3 seconds. And as the time goes by, it gets slower and can cost more than 10 seconds. We check the spark log, the sql job actually costs less than 1 second, usually 0.2 ~ 0.6 sec.
We try parquet before Orc, and also enlarge the executor memory from 1G to 2G. There is no great difference. The Hive table is not partitioned.
What might be the key issue?
python performance apache-spark hive
python performance apache-spark hive
asked Nov 26 '18 at 9:56
passingerpassinger
75110
asked Nov 26 '18 at 9:56
passingerpassinger
75110
asked Nov 26 '18 at 9:56
passingerpassinger
75110
asked Nov 26 '18 at 9:56
passingerpassinger
75110
asked Nov 26 '18 at 9:56
passingerpassinger
75110
75110
add a comment |
add a comment |
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