Hi,
Piggybacking on this discussion.
I'm trying to achieve the same, reading a csv file, from RStudio. Where I'm
stuck is how to supply some additional package from RStudio to spark.init()
as sparkR.init does() not provide an option to specify additional package.
I tried following codefrom RStudio. It is giving me error "Error in
callJMethod(sqlContext, "load", source, options) :
Invalid jobj 1. If SparkR was restarted, Spark operations need to be
re-executed."
------
Sys.setenv(SPARK_HOME="C:\\spark-1.4.0-bin-hadoop2.6")
.libPaths(c(file.path(Sys.getenv("SPARK_HOME"), "R", "lib"),.libPaths()))
library(SparkR)
sparkR.stop()
sc <- sparkR.init(master="local[2]", sparkEnvir =
list(spark.executor.memory="1G"),
sparkJars="C:\\spark-1.4.0-bin-hadoop2.6\\lib\\spark-csv_2.11-1.1.0.jar")
/* I have downloaded this spark-csv jar and kept it in lib folder of Spark
*/
sqlContext <- sparkRSQL.init(sc)
plutoMN <- read.df(sqlContext,
"C:\\Users\\Sourav\\Work\\SparkDataScience\\PlutoMN.csv", source =
"com.databricks.spark.csv").
------
However, I also tried this from shell as 'sparkR --package
com.databricks:spark-csv_2.11:1.1.0". This time I used the following code
and it works all fine.
sqlContext <- sparkRSQL.init(sc)
plutoMN <- read.df(sqlContext,
"C:\\Users\\Sourav\\Work\\SparkDataScience\\PlutoMN.csv", source =
"com.databricks.spark.csv").
Any idea how to achieve the same from RStudio ?
Regards,
On Thu, Jun 25, 2015 at 2:38 PM, Wei Zhou <zhweisop...@gmail.com> wrote:
> I tried out the solution using spark-csv package, and it worked fine now
> :) Thanks. Yes, I'm playing with a file with all columns as String, but the
> real data I want to process are all doubles. I'm just exploring what sparkR
> can do versus regular scala spark, as I am by heart a R person.
>
> 2015-06-25 14:26 GMT-07:00 Eskilson,Aleksander <alek.eskil...@cerner.com>:
>
>> Sure, I had a similar question that Shivaram was able fast for me, the
>> solution is implemented using a separate DataBrick’s library. Check out
>> this thread from the email archives [1], and the read.df() command [2]. CSV
>> files can be a bit tricky, especially with inferring their schemas. Are you
>> using just strings as your column types right now?
>>
>> Alek
>>
>> [1] --
>> http://apache-spark-developers-list.1001551.n3.nabble.com/CSV-Support-in-SparkR-td12559.html
>> [2] -- https://spark.apache.org/docs/latest/api/R/read.df.html
>>
>> From: Wei Zhou <zhweisop...@gmail.com>
>> Date: Thursday, June 25, 2015 at 4:15 PM
>> To: "shiva...@eecs.berkeley.edu" <shiva...@eecs.berkeley.edu>
>> Cc: Aleksander Eskilson <alek.eskil...@cerner.com>, "
>> user@spark.apache.org" <user@spark.apache.org>
>> Subject: Re: sparkR could not find function "textFile"
>>
>> Thanks to both Shivaram and Alek. Then if I want to create DataFrame
>> from comma separated flat files, what would you recommend me to do? One way
>> I can think of is first reading the data as you would do in r, using
>> read.table(), and then create spark DataFrame out of that R dataframe, but
>> it is obviously not scalable.
>>
>>
>> 2015-06-25 13:59 GMT-07:00 Shivaram Venkataraman <
>> shiva...@eecs.berkeley.edu>:
>>
>>> The `head` function is not supported for the RRDD that is returned by
>>> `textFile`. You can run `take(lines, 5L)`. I should add a warning here that
>>> the RDD API in SparkR is private because we might not support it in the
>>> upcoming releases. So if you can use the DataFrame API for your application
>>> you should try that out.
>>>
>>> Thanks
>>> Shivaram
>>>
>>> On Thu, Jun 25, 2015 at 1:49 PM, Wei Zhou <zhweisop...@gmail.com> wrote:
>>>
>>>> Hi Alek,
>>>>
>>>> Just a follow up question. This is what I did in sparkR shell:
>>>>
>>>> lines <- SparkR:::textFile(sc, "./README.md")
>>>> head(lines)
>>>>
>>>> And I am getting error:
>>>>
>>>> "Error in x[seq_len(n)] : object of type 'S4' is not subsettable"
>>>>
>>>> I'm wondering what did I do wrong. Thanks in advance.
>>>>
>>>> Wei
>>>>
>>>> 2015-06-25 13:44 GMT-07:00 Wei Zhou <zhweisop...@gmail.com>:
>>>>
>>>>> Hi Alek,
>>>>>
>>>>> Thanks for the explanation, it is very helpful.
>>>>>
>>>>> Cheers,
>>>>> Wei
>>>>>
>>>>> 2015-06-25 13:40 GMT-07:00 Eskilson,Aleksander <
>>>>> alek.eskil...@cerner.com>:
>>>>>
>>>>>> Hi there,
>>>>>>
>>>>>> The tutorial you’re reading there was written before the merge of
>>>>>> SparkR for Spark 1.4.0
>>>>>> For the merge, the RDD API (which includes the textFile() function)
>>>>>> was made private, as the devs felt many of its functions were too low
>>>>>> level. They focused instead on finishing the DataFrame API which supports
>>>>>> local, HDFS, and Hive/HBase file reads. In the meantime, the devs are
>>>>>> trying to determine which functions of the RDD API, if any, should be
>>>>>> made
>>>>>> public again. You can see the rationale behind this decision on the
>>>>>> issue’s
>>>>>> JIRA [1].
>>>>>>
>>>>>> You can still make use of those now private RDD functions by
>>>>>> prepending the function call with the SparkR private namespace, for
>>>>>> example, you’d use
>>>>>> SparkR:::textFile(…).
>>>>>>
>>>>>> Hope that helps,
>>>>>> Alek
>>>>>>
>>>>>> [1] -- https://issues.apache.org/jira/browse/SPARK-7230
>>>>>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__issues.apache.org_jira_browse_SPARK-2D7230&d=AwMFaQ&c=NRtzTzKNaCCmhN_9N2YJR-XrNU1huIgYP99yDsEzaJo&r=0vZw1rBdgaYvDJYLyKglbrax9kvQfRPdzxLUyWSyxPM&m=x60a-3ztBe4XOw2bOnEI9-Mc6mENXT8PVxYvsmTLVG8&s=HpX1Cpayu5Mwu9JVt2znimJyUwtV3vcPurUO9ZJhASo&e=>
>>>>>>
>>>>>> From: Wei Zhou <zhweisop...@gmail.com>
>>>>>> Date: Thursday, June 25, 2015 at 3:33 PM
>>>>>> To: "user@spark.apache.org" <user@spark.apache.org>
>>>>>> Subject: sparkR could not find function "textFile"
>>>>>>
>>>>>> Hi all,
>>>>>>
>>>>>> I am exploring sparkR by activating the shell and following the
>>>>>> tutorial here https://amplab-extras.github.io/SparkR-pkg/
>>>>>> <https://urldefense.proofpoint.com/v2/url?u=https-3A__amplab-2Dextras.github.io_SparkR-2Dpkg_&d=AwMFaQ&c=NRtzTzKNaCCmhN_9N2YJR-XrNU1huIgYP99yDsEzaJo&r=0vZw1rBdgaYvDJYLyKglbrax9kvQfRPdzxLUyWSyxPM&m=aL4A2Pv9tHbhgJUX-EnuYx2HntTnrqVpegm6Ag-FwnQ&s=qfOET1UvP0ECAKgnTJw8G13sFTi_PhiJ8Q89fMSgH_Q&e=>
>>>>>>
>>>>>> And when I tried to read in a local file with textFile(sc,
>>>>>> "file_location"), it gives an error could not find function "textFile".
>>>>>>
>>>>>> By reading through sparkR doc for 1.4, it seems that we need
>>>>>> sqlContext to import data, for example.
>>>>>>
>>>>>> people <- read.df(sqlContext,
>>>>>> "./examples/src/main/resources/people.json", "json"
>>>>>>
>>>>>> )
>>>>>> And we need to specify the file type.
>>>>>>
>>>>>> My question is does sparkR stop supporting general type file
>>>>>> importing? If not, would appreciate any help on how to do this.
>>>>>>
>>>>>> PS, I am trying to recreate the word count example in sparkR, and
>>>>>> want to import README.md file, or just any file into sparkR.
>>>>>>
>>>>>> Thanks in advance.
>>>>>>
>>>>>> Best,
>>>>>> Wei
>>>>>>
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>>>>>
>>>>>
>>>>
>>>
>>
>
