You can check my comment below the answer at
http://stackoverflow.com/a/30959388/4577954. BTW we added a new option to
sparkR.init to pass in packages and that should be a part of 1.5
Shivaram
On Wed, Jul 1, 2015 at 10:03 AM, Sourav Mazumder <
sourav.mazumde...@gmail.com> wrote:
> 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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>>>>
>>>
>>
>
