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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2015/05/12 12:26:00 UTC
[jira] [Assigned] (SPARK-7150) SQLContext.range()
[ https://issues.apache.org/jira/browse/SPARK-7150?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-7150:
-----------------------------------
Assignee: Adrian Wang (was: Apache Spark)
> SQLContext.range()
> ------------------
>
> Key: SPARK-7150
> URL: https://issues.apache.org/jira/browse/SPARK-7150
> Project: Spark
> Issue Type: Sub-task
> Components: ML, SQL
> Reporter: Joseph K. Bradley
> Assignee: Adrian Wang
> Priority: Minor
> Labels: starter
>
> It would be handy to have easy ways to construct random columns for DataFrames. Proposed API:
> {code}
> class SQLContext {
> // Return a DataFrame with a single column named "id" that has consecutive value from 0 to n.
> def range(n: Long): DataFrame
> def range(n: Long, numPartitions: Int): DataFrame
> }
> {code}
> Usage:
> {code}
> // uniform distribution
> ctx.range(1000).select(rand())
> // normal distribution
> ctx.range(1000).select(randn())
> {code}
> We should add an RangeIterator that supports long start/stop position, and then use it to create an RDD as the basis for this DataFrame.
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