Re: Spark SQL groupby timestamp

becomes very simple: select 3600*floor(timestamp/3600) as timestamp, count(error) as errors,from logsgroup by 3600*floor(timestamp/3600) Hope this helps./Sim -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Spark-SQL-groupby-timestamp-tp23470p23615.html Sent

Re: Spark SQL - groupby

Hi, Can someone provide me pointers for this issue. Thanks Subacini On Wed, Jul 2, 2014 at 3:34 PM, Subacini B subac...@gmail.com wrote: Hi, Below code throws compilation error , not found: *value Sum* . Can someone help me on this. Do i need to add any jars or imports ? even for Count

Re: Spark SQL - groupby

Hi, You need to import Sum and Count like: import org.apache.spark.sql.catalyst.expressions.{Sum,Count} // or with wildcard _ or if you use current master branch build, you can use sum('colB) instead of Sum('colB). Thanks. 2014-07-03 16:09 GMT+09:00 Subacini B subac...@gmail.com: Hi, Can

Spark SQL - groupby

Hi, Below code throws compilation error , not found: *value Sum* . Can someone help me on this. Do i need to add any jars or imports ? even for Count , same error is thrown val queryResult = sql(select * from Table) queryResult.groupBy('colA)('colA,*Sum*('colB) as 'totB).aggregate(*Sum*