RE: DataFrame#show cost 2 Spark Jobs ?
Ok, I see, thanks for the correction, but this should be optimized. From: Shixiong Zhu [mailto:zsxw...@gmail.com] Sent: Tuesday, August 25, 2015 2:08 PM To: Cheng, Hao Cc: Jeff Zhang; user@spark.apache.org Subject: Re: DataFrame#show cost 2 Spark Jobs ? That's two jobs. `SparkPlan.executeTake` will call `runJob` twice in this case. Best Regards, Shixiong Zhu 2015-08-25 14:01 GMT+08:00 Cheng, Hao hao.ch...@intel.commailto:hao.ch...@intel.com: O, Sorry, I miss reading your reply! I know the minimum tasks will be 2 for scanning, but Jeff is talking about 2 jobs, not 2 tasks. From: Shixiong Zhu [mailto:zsxw...@gmail.commailto:zsxw...@gmail.com] Sent: Tuesday, August 25, 2015 1:29 PM To: Cheng, Hao Cc: Jeff Zhang; user@spark.apache.orgmailto:user@spark.apache.org Subject: Re: DataFrame#show cost 2 Spark Jobs ? 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.commailto: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.commailto:zjf...@gmail.com] Sent: Tuesday, August 25, 2015 8:11 AM To: Cheng, Hao Cc: user@spark.apache.orgmailto: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.jsonfile:///\\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.commailto: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.commailto:zjf...@gmail.com] Sent: Monday, August 24, 2015 6:20 PM To: user@spark.apache.orgmailto: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
RE: DataFrame#show cost 2 Spark Jobs ?
O, Sorry, I miss reading your reply! I know the minimum tasks will be 2 for scanning, but Jeff is talking about 2 jobs, not 2 tasks. From: Shixiong Zhu [mailto:zsxw...@gmail.com] Sent: Tuesday, August 25, 2015 1:29 PM To: Cheng, Hao Cc: Jeff Zhang; user@spark.apache.org Subject: Re: DataFrame#show cost 2 Spark Jobs ? 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.commailto: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.commailto:zjf...@gmail.com] Sent: Tuesday, August 25, 2015 8:11 AM To: Cheng, Hao Cc: user@spark.apache.orgmailto: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.jsonfile:///\\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.commailto: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.commailto:zjf...@gmail.com] Sent: Monday, August 24, 2015 6:20 PM To: user@spark.apache.orgmailto: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
Re: DataFrame#show cost 2 Spark Jobs ?
That's two jobs. `SparkPlan.executeTake` will call `runJob` twice in this case. Best Regards, Shixiong Zhu 2015-08-25 14:01 GMT+08:00 Cheng, Hao hao.ch...@intel.com: O, Sorry, I miss reading your reply! I know the minimum tasks will be 2 for scanning, but Jeff is talking about 2 jobs, not 2 tasks. *From:* Shixiong Zhu [mailto:zsxw...@gmail.com] *Sent:* Tuesday, August 25, 2015 1:29 PM *To:* Cheng, Hao *Cc:* Jeff Zhang; user@spark.apache.org *Subject:* Re: DataFrame#show cost 2 Spark Jobs ? 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
RE: DataFrame#show cost 2 Spark Jobs ?
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
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
Re: DataFrame#show cost 2 Spark Jobs ?
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
RE: DataFrame#show cost 2 Spark Jobs ?
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.jsonfile:///\\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.commailto: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.commailto:zjf...@gmail.com] Sent: Monday, August 24, 2015 6:20 PM To: user@spark.apache.orgmailto: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
Re: DataFrame#show cost 2 Spark Jobs ?
Because defaultMinPartitions is 2 (See https://github.com/apache/spark/blob/642c43c81c835139e3f35dfd6a215d668a474203/core/src/main/scala/org/apache/spark/SparkContext.scala#L2057 ), your input people.json will be split to 2 partitions. At first, `take` will start a job for the first partition. However, the limit is 21, but the first partition only has 2 records. So it will continue to start a new job for the second partition. You can check implementation details in SparkPlan.executeTake: https://github.com/apache/spark/blob/642c43c81c835139e3f35dfd6a215d668a474203/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala#L185 Best Regards, Shixiong Zhu 2015-08-25 8:11 GMT+08:00 Jeff Zhang zjf...@gmail.com: 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
