Hao,
I can reproduce it using the master branch. I'm curious why you cannot
reproduce it. Did you check if the input HadoopRDD did have two partitions?
My test code is
val df = sqlContext.read.json("examples/src/main/resources/people.json")
df.show()
Best Regards,
Shixiong Zhu
2015-08-25 13:01 GMT+08:00 Cheng, Hao <hao.ch...@intel.com>:
> Hi Jeff, which version are you using? I couldn’t reproduce the 2 spark
> jobs in the `df.show()` with latest code, we did refactor the code for json
> data source recently, not sure you’re running an earlier version of it.
>
>
>
> And a known issue is Spark SQL will try to re-list the files every time
> when loading the data for JSON, it’s probably causes longer time for ramp
> up with large number of files/partitions.
>
>
>
> *From:* Jeff Zhang [mailto:zjf...@gmail.com]
> *Sent:* Tuesday, August 25, 2015 8:11 AM
> *To:* Cheng, Hao
> *Cc:* user@spark.apache.org
> *Subject:* Re: DataFrame#show cost 2 Spark Jobs ?
>
>
>
> Hi Cheng,
>
>
>
> I know that sqlContext.read will trigger one spark job to infer the
> schema. What I mean is DataFrame#show cost 2 spark jobs. So overall it
> would cost 3 jobs.
>
>
>
> Here's the command I use:
>
>
>
> >> val df = sqlContext.read.json("
> file:///Users/hadoop/github/spark/examples/src/main/resources/people.json")
> // trigger one spark job to infer schema
>
> >> df.show() // trigger 2 spark jobs which is weird
>
>
>
>
>
>
>
>
>
> On Mon, Aug 24, 2015 at 10:56 PM, Cheng, Hao <hao.ch...@intel.com> wrote:
>
> The first job is to infer the json schema, and the second one is what you
> mean of the query.
>
> You can provide the schema while loading the json file, like below:
>
>
>
> sqlContext.read.schema(xxx).json(“…”)?
>
>
>
> Hao
>
> *From:* Jeff Zhang [mailto:zjf...@gmail.com]
> *Sent:* Monday, August 24, 2015 6:20 PM
> *To:* user@spark.apache.org
> *Subject:* DataFrame#show cost 2 Spark Jobs ?
>
>
>
> It's weird to me that the simple show function will cost 2 spark jobs.
> DataFrame#explain shows it is a very simple operation, not sure why need 2
> jobs.
>
>
>
> == Parsed Logical Plan ==
>
> Relation[age#0L,name#1]
> JSONRelation[file:/Users/hadoop/github/spark/examples/src/main/resources/people.json]
>
>
>
> == Analyzed Logical Plan ==
>
> age: bigint, name: string
>
> Relation[age#0L,name#1]
> JSONRelation[file:/Users/hadoop/github/spark/examples/src/main/resources/people.json]
>
>
>
> == Optimized Logical Plan ==
>
> Relation[age#0L,name#1]
> JSONRelation[file:/Users/hadoop/github/spark/examples/src/main/resources/people.json]
>
>
>
> == Physical Plan ==
>
> Scan
> JSONRelation[file:/Users/hadoop/github/spark/examples/src/main/resources/people.json][age#0L,name#1]
>
>
>
>
>
>
>
> --
>
> Best Regards
>
> Jeff Zhang
>
>
>
>
>
> --
>
> Best Regards
>
> Jeff Zhang
>
