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From "Eskilson,Aleksander" <>
Subject Re: CSV Support in SparkR
Date Tue, 02 Jun 2015 21:20:49 GMT
Seems to work great in the master build. It’s really good to have this functionality.

Alek Eskilson

From: <Eskilson>, Aleksander Eskilson <<>>
Date: Tuesday, June 2, 2015 at 2:59 PM
To: "<>" <<>>
Cc: Burak Yavuz <<>>, "<>"
Subject: Re: CSV Support in SparkR

Ah, alright, cool. I’ll rebuild and let you know.

Thanks again,

From: Shivaram Venkataraman <<>>
Reply-To: "<>" <<>>
Date: Tuesday, June 2, 2015 at 2:57 PM
To: Aleksander Eskilson <<>>
Cc: "<>" <<>>,
Burak Yavuz <<>>, "<>"
Subject: Re: CSV Support in SparkR

There was a bug in the SparkContext creation that I fixed yesterday.<>

If you build from master it should be fixed. Also I think we might have a rc4 which should
have this


On Tue, Jun 2, 2015 at 12:56 PM, Eskilson,Aleksander <<>>
Hey, that’s pretty convenient. Unfortunately, although the package seems to pull fine into
the session, I’m getting class not found exceptions with:

Caused by: org.apache.spark.SparkExcetion: Job aborted due to stage failure: Task 0 in stage
6.0 failed 4 times, most recent failure: Lost task 0.3 in stage 6.0: java.lang.ClassNotFoundException:

Which smells like a path issue to me, and I made sure the ivy repo was part of my PATH, but
functions like showDF() still fail with that error. Did I miss a setting, or should the package
inclusion in the sparkR execution load that in?

I’ve run
df <- read.df(sqlCtx, “./data.csv”, “com.databricks.spark.csv”, header=“true”,
showDF(df, 10)

(my data is pipeline delimited, and the default SQL context is sqlCtx)


From: Shivaram Venkataraman <<>>
Reply-To: "<>" <<>>
Date: Tuesday, June 2, 2015 at 2:08 PM
To: Burak Yavuz <<>>
Cc: Aleksander Eskilson <<>>,
"<>" <<>>,
Shivaram Venkataraman <<>>
Subject: Re: CSV Support in SparkR

Hi Alek

As Burak said, you can already use the spark-csv with SparkR in the 1.4 release. So right
now I use it with something like this

# Launch SparkR
./bin/sparkR --packages com.databricks:spark-csv_2.10:1.0.3
df <- read.df(sqlContext, "./nycflights13.csv", "com.databricks.spark.csv", header="true")

You can also pass in other options to the spark csv as arguments to `read.df`. Let us know
if this works


On Tue, Jun 2, 2015 at 12:03 PM, Burak Yavuz <<>>

cc'ing Shivaram here, because he worked on this yesterday.

If I'm not mistaken, you can use the following workflow:
```./bin/sparkR --packages com.databricks:spark-csv_2.10:1.0.3```

and then

```df <- read.df(sqlContext, "/data", "csv", header = "true")```


On Tue, Jun 2, 2015 at 11:52 AM, Eskilson,Aleksander <<>>
Are there any intentions to provide first class support for CSV files as one of the loadable
file types in SparkR? Data brick’s spark-csv API [1] has support for SQL, Python, and Java/Scala,
and implements most of the arguments of R’s read.table API [2], but currently there is no
way to load CSV data in SparkR (1.4.0) besides separating our headers from the data, loading
into an RDD, splitting by our delimiter, and then converting to a SparkR Data Frame with a
vector of the columns gathered from the header.

Alek Eskilson

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