On 28 Sep 2017, at 15:27, Daniel Siegmann
mailto:dsiegm...@securityscorecard.io>> wrote:
Can you kindly explain how Spark uses parallelism for bigger (say 1GB) text
file? Does it use InputFormat do create multiple splits and creates 1 partition
per split? Also, in case of S3 or NFS, how does
> On 28 Sep 2017, at 14:45, ayan guha wrote:
>
> Hi
>
> Can you kindly explain how Spark uses parallelism for bigger (say 1GB) text
> file? Does it use InputFormat do create multiple splits and creates 1
> partition per split?
Yes, Input formats give you their splits, this is usually used to
Vadim's "scheduling within an application" approach turned out to be
excellent, at least on a single node with the CPU usage reaching about
90%. I directly implemented the code template that Vadim kindly
provided:
parallel_collection_paths.foreach(
path => {
val lines = spa
Hi Jeroen,
I do not believe that I completely agree with the idea that you will be
spending more time and memory that way.
But if that was also the case why are you not using data frames and UDF?
Regards,
Gourav
On Sun, Oct 1, 2017 at 6:17 PM, Jeroen Miller
wrote:
> On Fri, Sep 29, 2017 at 1
Hammad,
The recommended way to implement this logic would be to:
Create a SparkSession.
Create a Streaming Context using the SparkContext embedded in the
SparkSession
Use the single SparkSession instance for the SQL operations within the
foreachRDD.
It's important to note that spark operations c
Hi
The question is getting to the list.
I have no experience in hbase ...though , having seen similar stuff when
saving a df somewhere else...it might have to do with the properties you
need to set to let spark know it is dealing with hbase? Don't u need to set
some properties on the spark context
Hello,
*Background:*
I have Spark Streaming context;
SparkConf conf = new
SparkConf().setMaster("local[2]").setAppName("TransformerStreamPOC");
conf.set("spark.driver.allowMultipleContexts", "true"); *<== this*
JavaStreamingContext jssc = new JavaStreamingContext(conf,
Durations.seconds(60));
On Fri, Sep 29, 2017 at 12:20 AM, Gourav Sengupta
wrote:
> Why are you not using JSON reader of SPARK?
Since the filter I want to perform is so simple, I do not want to
spend time and memory to deserialise the JSON lines.
Jeroen
--
Hello,
Is there a way to find the DDL of the “temporary” view created in current
session with spark sql:
For example :
create or replace temporary view
tmp_v as
select
c1 from table table_x;
“Show create table “ does not work for this case as it is not a table .
“Describe” could show the c
Hi,
Set the inferschema option to true in spark-csv. you may also want to set
the mode option. See readme below
https://github.com/databricks/spark-csv/blob/master/README.md
Best,
Anastasios
Am 01.10.2017 07:58 schrieb "Kanagha Kumar" :
Hi,
I'm trying to read data from HDFS in spark as datafr
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