Hello,
I have written an Spark SQL application which reads data from HDFS and
query on it.
The data size is around 2GB (30 million records). The schema and query I am
running is as below.
The query takes around 05+ seconds to execute.
I tried by adding
rdd.persist(StorageLevel.MEMORY_AND_DISK)
and
rdd.cache()
but in both the cases it takes extra time, even if I give the below query as
second the data. (assuming Spark will cache it for first query).
case class EventDataTbl(ID: String,
ONum: String,
RNum: String,
Timestamp: String,
Duration: String,
Type: String,
Source: String,
OName: String,
RName: String)
sql("SELECT COUNT(*) AS Frequency,ONum,OName,RNum,RName FROM EventDataTbl
GROUP BY ONum,OName,RNum,RName ORDER BY Frequency DESC LIMIT
10").collect().foreach(println)
Can you let me know if I am missing anything ?
Thanks,
Shailesh
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