Hi,
Curious and curious. I'm puzzled by the Spark SQL cached table.
Theoretically, the cached table should be columnar table, and only scan
the column that included in my SQL.
However, in my test, I always see the whole table is scanned even though
I only "select" one column in my SQL.
Here is my code:
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
import sqlContext._
sqlContext.jsonFile("/data/ad.json").registerTempTable("adTable")
sqlContext.cacheTable("adTable") //The table has > 10 columns
//First run, cache the table into memory
sqlContext.sql("select * from adTable").collect
//Second run, only one column is used. It should only scan a small fraction of
data
sqlContext.sql("select adId from adTable").collect sqlContext.sql("select adId
from adTable").collect
sqlContext.sql("select adId from adTable").collect
What I found is, every time I run the SQL, in WEB UI, it shows the
total amount of input data is always the same --- the total amount of the table.
Is anything wrong? My expectation is: 1. The cached table is
stored as columnar table 2. Since I only need one column in my SQL, the
total amount of input data showed in WEB UI should be very small
But what I found is totally not the case. Why?
Thanks
