Thank you for your help. "toDF()" solved my first problem. And, the second issue was a non-issue, since the second example worked without any modification.
David On Sun, Mar 15, 2015 at 1:37 AM, Rishi Yadav <ri...@infoobjects.com> wrote: > programmatically specifying Schema needs > > import org.apache.spark.sql.type._ > > for StructType and StructField to resolve. > > On Sat, Mar 14, 2015 at 10:07 AM, Sean Owen <so...@cloudera.com> wrote: > >> Yes I think this was already just fixed by: >> >> https://github.com/apache/spark/pull/4977 >> >> a ".toDF()" is missing >> >> On Sat, Mar 14, 2015 at 4:16 PM, Nick Pentreath >> <nick.pentre...@gmail.com> wrote: >> > I've found people.toDF gives you a data frame (roughly equivalent to the >> > previous Row RDD), >> > >> > And you can then call registerTempTable on that DataFrame. >> > >> > So people.toDF.registerTempTable("people") should work >> > >> > >> > >> > — >> > Sent from Mailbox >> > >> > >> > On Sat, Mar 14, 2015 at 5:33 PM, David Mitchell < >> jdavidmitch...@gmail.com> >> > wrote: >> >> >> >> >> >> I am pleased with the release of the DataFrame API. However, I started >> >> playing with it, and neither of the two main examples in the >> documentation >> >> work: http://spark.apache.org/docs/1.3.0/sql-programming-guide.html >> >> >> >> Specfically: >> >> >> >> Inferring the Schema Using Reflection >> >> Programmatically Specifying the Schema >> >> >> >> >> >> Scala 2.11.6 >> >> Spark 1.3.0 prebuilt for Hadoop 2.4 and later >> >> >> >> Inferring the Schema Using Reflection >> >> scala> people.registerTempTable("people") >> >> <console>:31: error: value registerTempTable is not a member of >> >> org.apache.spark >> >> .rdd.RDD[Person] >> >> people.registerTempTable("people") >> >> ^ >> >> >> >> Programmatically Specifying the Schema >> >> scala> val peopleDataFrame = sqlContext.createDataFrame(people, schema) >> >> <console>:41: error: overloaded method value createDataFrame with >> >> alternatives: >> >> (rdd: org.apache.spark.api.java.JavaRDD[_],beanClass: >> >> Class[_])org.apache.spar >> >> k.sql.DataFrame <and> >> >> (rdd: org.apache.spark.rdd.RDD[_],beanClass: >> >> Class[_])org.apache.spark.sql.Dat >> >> aFrame <and> >> >> (rowRDD: >> >> org.apache.spark.api.java.JavaRDD[org.apache.spark.sql.Row],columns: >> >> java.util.List[String])org.apache.spark.sql.DataFrame <and> >> >> (rowRDD: >> >> org.apache.spark.api.java.JavaRDD[org.apache.spark.sql.Row],schema: o >> >> rg.apache.spark.sql.types.StructType)org.apache.spark.sql.DataFrame >> <and> >> >> (rowRDD: org.apache.spark.rdd.RDD[org.apache.spark.sql.Row],schema: >> >> org.apache >> >> .spark.sql.types.StructType)org.apache.spark.sql.DataFrame >> >> cannot be applied to (org.apache.spark.rdd.RDD[String], >> >> org.apache.spark.sql.ty >> >> pes.StructType) >> >> val df = sqlContext.createDataFrame(people, schema) >> >> >> >> Any help would be appreciated. >> >> >> >> David >> >> >> > >> >> --------------------------------------------------------------------- >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> For additional commands, e-mail: user-h...@spark.apache.org >> >> > -- ### Confidential e-mail, for recipient's (or recipients') eyes only, not for distribution. ###
