Hello, All,
I found the examples for JDBC connection are mostly read the whole table
and then do operations like joining.
val jdbcDF = sqlContext.read.format("jdbc").options(
Map("url" -> "jdbc:postgresql:dbserver",
"dbtable" -> "schema.tablename")).load()
Sometimes it is not practical sinc
Hello, All,
I found the examples for JDBC connection are mostly read the whole table
and then do operations like joining.
val jdbcDF = sqlContext.read.format("jdbc").options(
Map("url" -> "jdbc:postgresql:dbserver",
"dbtable" -> "schema.tablename")).load()
Sometimes it is not practical sinc
Hello, all,
I am wondering if anyone tried time series prediction using spark?
Any good practice to suggest me? Thanks a lot!
--
Best regards!
Lin,Cui
What's the best way to import data from Oracle to Spark? Thanks!
--
Best regards!
Lin,Cui
Hello,
I got stuck in adding spark sql into my standalone application.
The build.sbt is defined as:
libraryDependencies += "org.apache.spark" %% "spark-core" % "1.4.1"
I got the following error when building the package:
*[error] /data/workspace/test/src/main/scala/TestMain.scala:6: object
sql
% "1.4.1"
>
> Though, I would consider using spark-hive and HiveContext, as the query
> parser is more powerful and you'll have access to window functions and other
> features.
>
>
> On Thu, Sep 17, 2015 at 10:59 AM, Cui Lin wrote:
>
>> Hello,
>>
Hello,All,
Parsing JSON's nested structure is easy if using Java or Python API. Where
I can find the similar way to parse JSON file using spark?
Another question is by using SparkSQL, how can i easily save the results
into NOSQL DB? any examples? Thanks a lot!
--
Best regards!
Lin,Cui
).foreach(line => System.out.println(line))
>
>val jsonMessage = sqlContext.jsonRDD(anotherPeopleRDD)
>
>jsonMessage.toArray().foreach(line => System.out.println(line))
>
>jsonMessage.registerTempTable("peopl
I firstly tried simply copy the codes below into spark application that has
codes working with kafka streaming.
No any result can be printed into system console, then I tried spark shell, and
it works. I can’t figured out the reason.
Best regards,
Cui Lin
From: Tobias Pfeiffer mailto:t
columns
in the json formatted message.
Thanks for your help!
Best regards,
Cui Lin
columns.
Is there any way to get column name instead of hard code “time” in this case?
mapper.readValue[Map[String,Any]](x).get("time")
Best regards,
Cui Lin
From: Helena Edelson
mailto:helena.edel...@datastax.com>>
Date: Thursday, March 5, 2015 at 7:02 AM
To: Ted Yu mailto:yuz
Hi, Ted,
Thanks for your reply. I noticed from the below link partitions.size will not
work for checking empty RDD in streams. It seems that the problem can be solved
in spark 1.3 which is no way to download at this time?
https://issues.apache.org/jira/browse/SPARK-5270
Best regards,
Cui Lin
No woder I had out of memory issue before…
I doubt if we really need such configuration on production level…
Best regards,
Cui Lin
From: Krishna Sankar mailto:ksanka...@gmail.com>>
Date: Sunday, March 8, 2015 at 3:27 PM
To: Nasir Khan mailto:nasirkhan.onl...@gmail.com>&g
Dear all,
Could you send me a list for input data source that spark streaming could
support?
My list is HDFS, Kafka, textfile?…
I am wondering if spark streaming could directly read data from certain port
(443 e.g.) that my devices directly send to?
Best regards,
Cui Lin
Tathagata,
Thanks for your quick response. The link is helpful to me.
Do you know any API for streaming data from RMDB ?
Best regards,
Cui Lin
From: Tathagata Das mailto:t...@databricks.com>>
Date: Monday, March 9, 2015 at 11:28 AM
To: Cui Lin mailto:cui@hds.com>&g
sent from other host to that port were
ignored.
I can see all messages from “nc –l [port no.]", why such thing could happen?
Best regards,
Cui Lin
Hello, All,
What’s the best practice on deploying/publishing spark-based scientific
applications into a web service? Similar to Shiny on R.
Thanks!
Best regards,
Cui Lin
Thanks, Gaurav and Corey,
Probably I didn’t make myself clear. I am looking for best Spark practice
similar to Shiny for R, the analysis/visualziation results can be easily
published to web server and shown from web browser. Or any dashboard for Spark?
Best regards,
Cui Lin
From: gtinside
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