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https://issues.apache.org/jira/browse/SPARK-7150?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reynold Xin resolved SPARK-7150.
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Resolution: Fixed
Fix Version/s: 1.4.0
> 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
> Fix For: 1.4.0
>
>
> 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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