Hi all,
What is the best approach for iterating all columns in a pyspark
dataframe?I want to apply some conditions on all columns in the dataframe.
Currently I am using for loop for iteration. Is it a good practice while
using Spark and I am using Spark 3.0
Please advice
Thanks,
Devi
Hi all,
I am trying to run FP growth algorithm using spark and scala.sample input
dataframe is following,
+---+
|productName
Hi all,
I have a dataframe like following,
+-+--+
|client_id|Date |
+ +--+
| a |2016-11-23|
| b |2016-11-18|
| a |2016-11-23|
| a |2016-11-23|
| a |2016-11-24|
+-+--+
I want to find unique dates of each client_id
[client_id: string, ts:
>>> string, ts1: string]
>>>
>>> scala> finaldf.show
>>> ++-+---+
>>> | client_id| ts| ts1|
>>> ++-+---+
>>> |cd646551-fceb-416...|1477989416803|48805-08-14|
>
Hi,
Thanks for replying to my question.
I am using scala
On Mon, Dec 5, 2016 at 1:20 PM, Marco Mistroni <mmistr...@gmail.com> wrote:
> Hi
> In python you can use date time.fromtimestamp(..).
> strftime('%Y%m%d')
> Which spark API are you using?
> Kr
>
> O
Hi all,
I have a dataframe like following,
++---+
|client_id |timestamp|
++---+
|cd646551-fceb-4166-acbc-b9|1477989416803 |
|3bc61951-0f49-43bf-9848-b2|1477983725292 |
Hi all,
I have 4 data frames with three columns,
client_id,product_id,interest
I want to combine these 4 dataframes into one dataframe.I used union like
following
df1.union(df2).union(df3).union(df4)
But it is time consuming for bigdata.what is the optimized way for doing
this using spark 2.0
built.sbt.
Is my query wrong or anything else needed to import?
Please help.
On Sun, Oct 16, 2016 at 8:23 PM, Rodrick Brown <rodr...@orchardplatform.com>
wrote:
>
>
> On Sun, Oct 16, 2016 at 10:51 AM, Devi P.V <devip2...@gmail.com> wrote:
>
>> Hi all,
>> I am
Hi all,
I am trying to read data from couchbase using spark 2.0.0.I need to fetch
complete data from a bucket as Rdd.How can I solve this?Does spark 2.0.0
support couchbase?Please help.
Thanks
>
> --
> Oleksiy Dyagilev
>
> On Wed, Sep 7, 2016 at 9:42 AM, Devi P.V <devip2...@gmail.com> wrote:
>
>> I am newbie in CouchBase.I am trying to write data into CouchBase.My
>> sample code is following,
>>
>> val cfg = new SparkConf()
>
I am newbie in CouchBase.I am trying to write data into CouchBase.My sample
code is following,
val cfg = new SparkConf()
.setAppName("couchbaseQuickstart")
.setMaster("local[*]")
.set("com.couchbase.bucket.MyBucket","pwd")
val sc = new SparkContext(cfg)
val doc1 =
The following piece of code works for me to read data from S3 using Spark.
val conf = new SparkConf().setAppName("Simple
Application").setMaster("local[*]")
val sc = new SparkContext(conf)
val hadoopConf=sc.hadoopConfiguration;
hadoopConf.set("fs.s3.impl", "org.apache.hadoop.fs.s3native
;Courage doesn't always roar. Sometimes courage is the quiet voice at the
> end of the day saying I will try again"
>
>
>
> From:glen <cng...@126.com>
> To:"Devi P.V" <devip2...@gmail.com>
> Cc:"user@spark.apache.org" &
Hi all,
I am newbie in collaborative filtering.I want to implement collaborative
filtering algorithm(need to find top 10 recommended products) using Spark
and Scala.I have a rating dataset where userID & ProductID are String type.
UserID ProductID Rating
b3a68043-c1
Hi all,
I am trying to write a spark dataframe into MS-Sql Server.I have tried
using the following code,
val sqlprop = new java.util.Properties
sqlprop.setProperty("user","uname")
sqlprop.setProperty("password","pwd")
Hi all,
I am newbie in Power BI.What are the configurations need to connect Power
BI to spark on my local machine? I found some documents that mentioned
spark over Azure's HDInsight .But didn't find any reference materials for
connecting Spark to remote machine? Is it possible?
following is the
I want to multiply two large matrices (from csv files)using Spark and Scala
and save output.I use the following code
val rows=file1.coalesce(1,false).map(x=>{
val line=x.split(delimiter).map(_.toDouble)
Vectors.sparse(line.length,
line.zipWithIndex.map(e => (e._2,
Hi All,
I have a 5GB CSV dataset having 69 columns..I need to find the count of
distinct values in each column. What is the optimized way to find the same
using spark scala?
Example CSV format :
a,b,c,d
a,c,b,a
b,b,c,d
b,b,c,a
c,b,b,a
Output expecting :
(a,2),(b,2),(c,1) #- First column
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