Github user gatorsmile commented on the pull request:
https://github.com/apache/spark/pull/10335#issuecomment-165677516
New range API using logical/physical operators with `count` (workload
**1,000,000,000** rows):
```
scala> val startTime = System.currentTimeMillis; sqlContext.range(0,
1000000000, 1, 15).count(); val endTime = System.currentTimeMillis; val start =
new Timestamp(startTime); val end = new Timestamp(endTime); val elapsed =
(endTime - startTime)/ 1000.0
startTime: Long = 1450416360107
endTime: Long = 1450416368590
start: java.sql.Timestamp = 2015-12-17 21:26:00.107
end: java.sql.Timestamp = 2015-12-17 21:26:08.59
elapsed: Double = 8.483
scala> val startTime = System.currentTimeMillis; sqlContext.range(0,
1000000000, 1, 15).count(); val endTime = System.currentTimeMillis; val start =
new Timestamp(startTime); val end = new Timestamp(endTime); val elapsed =
(endTime - startTime)/ 1000.0
startTime: Long = 1450416371664
endTime: Long = 1450416380654
start: java.sql.Timestamp = 2015-12-17 21:26:11.664
end: java.sql.Timestamp = 2015-12-17 21:26:20.654
elapsed: Double = 8.99
scala> val startTime = System.currentTimeMillis; sqlContext.range(0,
1000000000, 1, 15).count(); val endTime = System.currentTimeMillis; val start =
new Timestamp(startTime); val end = new Timestamp(endTime); val elapsed =
(endTime - startTime)/ 1000.0
startTime: Long = 1450416383434
endTime: Long = 1450416392369
start: java.sql.Timestamp = 2015-12-17 21:26:23.434
end: java.sql.Timestamp = 2015-12-17 21:26:32.369
elapsed: Double = 8.935
```
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