Hi Gurus,
I am relatively new to Big Data and know some about Spark and Hive.
I was wondering do I need to pick up skills on Hbase as well. I am not sure how
it works but know that it is kind of columnar NoSQL database.
I know it is good to know something new in Big Data space. Just wondering if
Hi,
We intend to use 5servers which will be utilized for building Bigdata Hadoop
data warehousesystem (not using any propriety distribution like Hortonworks or
Cloudera orothers).All servers configurations are 512GB RAM, 30TB storageand 16
cores, Ubuntu Linux servers. Hadoop will be installed
experts,
please I need to understand how shuffling works in Spark and which parameters
influence it.
I am sorry but my knowledge of shuffling is very limited. Need a practical use
case if you can.
regards
Experts.
Please your valued advice.
I have spark 1.5.2 set up as standalone for now and I have started the master
as below
start-master.sh
I also have modified config/slave file to have
# A Spark Worker will be started on each of the machines listed below.
localhostworkerhost
On the localhost I
Gurus,
I would like to read a csv file into a Data Frame but able to rename the column
name, change a column type from String to Integer or drop the column from
further analysis before saving data as parquet file?
Thanks
Gurus,
If I register a temporary table as below
r.toDFres58: org.apache.spark.sql.DataFrame = [_1: string, _2: string, _3:
double, _4: double, _5: double]
r.toDF.registerTempTable("items")
sql("select * from items")res60: org.apache.spark.sql.DataFrame = [_1: string,
_2: string, _3: double, _4:
.(firstcolumn) in above when mapping if
possible so columns will have labels
On Thursday, 24 March 2016, 0:18, Michael Armbrust
wrote:
You probably need to use `backticks` to escape `_1` since I don't think that
its a valid SQL identifier.
On Wed, Mar 23, 2016 at 5:10 PM, Ash
reason is that for maps, we have to
>actually materialize and object to pass to your function. However, if you
>stick to column expression we can actually work directly on serialized data.
On Wed, Mar 23, 2016 at 5:27 PM, Ashok Kumar wrote:
thank you sir
sql("select `_1` as firstcolumn fro
Experts,
I would like to know when a table was created in Hive database using Spark
shell?
Thanks
umns: [] ]
[Sort Columns: [] ]
[Storage Desc Params: ]
[ serialization.format 1 ]
HTH
Dr Mich Talebzadeh LinkedIn
https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
http://talebzade
Hello Mich
If you accommodate can you please share your approach to steps 1-3 above.
Best regards
On Sunday, 27 March 2016, 14:53, Mich Talebzadeh
wrote:
Pretty simple as usual it is a combination of ETL and ELT.
Basically csv files are loaded into staging directory on host, compresse
ot;=== Checking that all files are moved to hdfs staging
directory"
hdfs dfs -ls ${DIR}
exit 0HTH
Dr Mich Talebzadeh LinkedIn
https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
http://talebzadehmich.wordpress.com
On 28 March 2016 at 22:24, Ashok Kumar wro
Experts,
One of terms used and I hear is N-tier architecture within Big Data used for
availability, performance etc. I also hear that Spark by means of its query
engine and in-memory caching fits into middle tier (application layer) with
HDFS and Hive may be providing the data tier. Can someone
concept or metastore. Thus it relies on others to
provide that service.
HTH
Dr Mich Talebzadeh LinkedIn
https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw
http://talebzadehmich.wordpress.com
On 29 March 2016 at 22:07, Ashok Kumar wrote:
Experts,
One of terms used
Hello,
How feasible is to use Spark to extract csv files and creates and writes the
content to an ORC table in a Hive database.
Is Parquet file the best (optimum) format to write to HDFS from Spark app.
Thanks
Hi
I like a simple sqrt operation on a list but I don't get the result
scala val l = List (1,5,786,25)l: List[Int] = List(1, 5, 786, 25)
scala> l.map(x => x * x)res42: List[Int] = List(1, 25, 617796, 625)
scala> l.map(x => x * x).sqrt:28: error: value sqrt is not a member of
List[Int]
Is simple streaming mean continuous streaming and windows streaming time window?
val ssc = new StreamingContext(sparkConf, Seconds(10))
thanks
Hi,
Anyone has suggestions how to create and copy Hive and Spark tables from
Production to UAT.
One way would be to copy table data to external files and then move the
external files to a local target directory and populate the tables in target
Hive with data.
Is there an easier way of doing so?
On Spark GUI I can see the list of Workers.
I always understood that workers are used by executors.
What is the relationship between workers and executors please. Is it one to one?
Thanks
Hi,
I hear that some saying that Hadoop is getting old and out of date and will be
replaced by Spark!
Does this make sense and if so how accurate is it?
Best
? David
From: Ashok Kumar [mailto:ashok34...@yahoo.com.INVALID]
Sent: Thursday, April 14, 2016 2:13 PM
To: User
Subject: Spark replacing Hadoop Hi, I hear that some saying that Hadoop
is getting old and out of date and will be replaced by Spark! Does this make
sense and if so how
Hi,
I have Spark 1.6.1 but I do bot know how to invoke SparkR so I can use R with
Spark.
Is there a s hell similar to spark-shell that supports R besides Scala please?
Thanks
Thanks Michael as I gathered for now it is a feature.
On Monday, 25 April 2016, 18:36, Michael Armbrust
wrote:
When you define a class inside of a method, it implicitly has a pointer to the
outer scope of the method. Spark doesn't have access to this scope, so this
makes it hard (imp
hi,
so if i have 10gb of streaming data coming in does it require 10gb of memory in
each node?
also in that case why do we need using
dstream.cache()
thanks
On Monday, 9 May 2016, 9:58, Saisai Shao wrote:
It depends on you to write the Spark application, normally if data is already
on
understanding you don't need to call cache() again.
On Mon, May 9, 2016 at 5:06 PM, Ashok Kumar wrote:
hi,
so if i have 10gb of streaming data coming in does it require 10gb of memory in
each node?
also in that case why do we need using
dstream.cache()
thanks
On Monday, 9 May 2016,
2016, 10:49, Saisai Shao wrote:
Pease see the inline comments.
On Mon, May 9, 2016 at 5:31 PM, Ashok Kumar wrote:
Thank you.
So If I create spark streaming then
- The streams will always need to be cached? It cannot be stored in
persistent storage
You don't need to cache
Hi Dr Mich,
I will be very keen to have a look at it and review if possible.
Please forward me a copy
Thanking you warmly
On Thursday, 12 May 2016, 11:08, Mich Talebzadeh
wrote:
Hi Al,,
Following the threads in spark forum, I decided to write up on configuration of
Spark including all
Hi,
How one can avoid having Spark spill over after filling the node's memory.
Thanks
Hi,
I would like to know the approach and tools please to get the full performance
for a Spark app running through Spark-shell and Spark-sumbit
- Through Spark GUI at 4040?
- Through OS utilities top, SAR
- Through Java tools like jbuilder etc
- Through integration Spark with moni
Hi Dr Mich,
This is very good news. I will be interested to know how Hive engages with
Spark as an engine. What Spark processes are used to make this work?
Thanking you
On Monday, 23 May 2016, 19:01, Mich Talebzadeh
wrote:
Have a look at this thread
Dr Mich Talebzadeh LinkedIn
https
Hello,
A newbie question.
Is it possible to use java code directly in spark shell without using maven to
build a jar file?
How can I switch from scala to java in spark shell?
Thanks
Hi,
I can do inserts from Spark on Hive tables. How about updates or deletes. They
are failing when I tried?
Thanking
hi all,
i know very little about the subject.
we would like to get streaming data from twitter and facebook.
so questions please may i
- what format is data from twitter. is it jason format
- can i use spark and spark streaming for analyzing data
- can data be fed in/streamed via kafka
Hi all,
Appreciate any advice on this. It is about scala
I have created a very basic Utilities.scala that contains a test class and
method. I intend to add my own classes and methods as I expand and make
references to these classes and methods in my other apps
class getCheckpointDirectory { def
org.apache.log4j.Loggerimport
org.apache.log4j.Levelimport ?
Thanks
On Sunday, 5 June 2016, 15:21, Ted Yu wrote:
At compilation time, you need to declare the dependence on
getCheckpointDirectory.
At runtime, you can use '--jars utilities-assembly-0.1-SNAPSHOT.jar' to pas
on the nete.g.
http://www.scala-sbt.org/0.13/docs/Scala-Files-Example.html
For #2,
import . getCheckpointDirectory
Cheers
On Sun, Jun 5, 2016 at 8:36 AM, Ashok Kumar wrote:
Thank you sir.
At compile time can I do something similar to
libraryDependencies += "org.apache.spark" %% "spar
cala/TwitterAnalyzer/build.sbt#L18-19)[warn] +-
scala:scala_2.10:1.0sbt.ResolveException: unresolved dependency:
com.databricks#apps.twitter_classifier;1.0.0: not found
Any ideas?
regards,
On Sunday, 5 June 2016, 22:22, Jacek Laskowski wrote:
On Sun, Jun 5, 2016 at 9:01 PM
Anyone can help me with this please
On Sunday, 5 June 2016, 11:06, Ashok Kumar wrote:
Hi all,
Appreciate any advice on this. It is about scala
I have created a very basic Utilities.scala that contains a test class and
method. I intend to add my own classes and methods as I expand and
Hi,
What is the difference between running Spark in Local mode or standalone mode?
Are they the same. If they are not which is best suited for non prod work.
I am also aware that one can run Spark in Yarn mode as well.
Thanks
er of launching a standalone
cluster either manually(by starting a master and workers by hand), or by using
the launch scripts provided with Spark package.
You can find more on this here.
HTH
| |
|
| Tariq, Mohammad
| about.me/mti |
|
| |
|
| |
On Sat, Jun 11, 2016 at 11:38 PM, Ashok
cluster managements.
Local mode is actually a standalone mode which everything runs on the single
local machine instead of remote clusters.
That is my understanding.
On Sat, Jun 11, 2016 at 12:40 PM, Ashok Kumar
wrote:
Thank you for grateful
I know I can start spark-shell by launching the
Hi,
I have been told Spark in Local mode is simplest for testing. Spark document
covers little on local mode except the cores used in --master local[k].
Where are the the driver program, executor and resources. Do I need to start
worker threads and how many app I can use safely without exceeding
and one executor
with `k`
threads.https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/local/LocalSchedulerBackend.scala#L94
// maropu
On Sun, Jun 19, 2016 at 5:39 PM, Ashok Kumar
wrote:
Hi,
I have been told Spark in Local mode is simplest for testing
Thank you all sirs
Appreciated Mich your clarification.
On Sunday, 19 June 2016, 19:31, Mich Talebzadeh
wrote:
Thanks Jonathan for your points
I am aware of the fact yarn-client and yarn-cluster are both depreciated (still
work in 1.6.1), hence the new nomenclature.
Bear in mind this
Hi,
I have a SQL server table with 500,000,000 rows with primary key (unique
clustered index) on ID column
If I load it through JDBC into a DataFrame and register it via
registerTempTable will the data will be in the order of ID in tempTable?
Thanks
Hi,
Looking at this presentation Hive on Spark is Blazing Fast ..
Which latest version of Spark can run as an engine for Hive please?
Thanks
P.S. I am aware of Hive on TEZ but that is not what I am interested here please
Warmest regards
With Spark caching which file format is best to use parquet or ORC
Obviously ORC can be used with Hive.
My question is whether Spark can use various file, stripe rowset statistics
stored in ORC file?
Otherwise to me both parquet and ORC are files simply kept on HDFS. They do not
offer any cachin
Hello gurus,
We are storing data externally on Amazon S3
What is the optimum or best way to use Spark as SQL engine to access data on S3?
Any info/write up will be greatly appreciated.
Regards
Thanks.
Will this presentation recorded as well?
Regards
On Wednesday, 6 July 2016, 22:38, Mich Talebzadeh
wrote:
Dear forum members
I will be presenting on the topic of "Running Spark on Hive or Hive on Spark,
your mileage varies" in Future of Data: London DetailsOrganized by:
Horton
jdbc tool like squirrel
On Fri, Jul 8, 2016 at 3:50 AM, Ashok Kumar
wrote:
Hello gurus,
We are storing data externally on Amazon S3
What is the optimum or best way to use Spark as SQL engine to access data on S3?
Any info/write up will be greatly appreciated.
Regards
--
Best Regards,
Ayan
is that using Spark SQL will be much faster?
regards
On Friday, 8 July 2016, 6:30, ayan guha wrote:
Yes, it can.
On Fri, Jul 8, 2016 at 3:03 PM, Ashok Kumar wrote:
thanks so basically Spark Thrift Server runs on a port much like beeline that
uses JDBC to connect to Hive?
Can Spark thr
Hi Mich,
Your recent presentation in London on this topic "Running Spark on Hive or Hive
on Spark"
Have you made any more interesting findings that you like to bring up?
If Hive is offering both Spark and Tez in addition to MR, what stopping one not
to use Spark? I still don't get why TEZ + LLAP
Any expert advice warmly acknowledged..
thanking yo
On Monday, 11 July 2016, 17:24, Ashok Kumar wrote:
Hi Gurus,
Advice appreciated from Hive gurus.
My colleague has been using Cassandra. However, he says it is too slow and not
user friendly/MongodDB as a doc databases is pretty neat
Thanks Mich looking forward to it :)
On Tuesday, 19 July 2016, 19:13, Mich Talebzadeh
wrote:
Hi all,
This will be in London tomorrow Wednesday 20th July starting at 18:00 hour for
refreshments and kick off at 18:30, 5 minutes walk from Canary Wharf Station,
Jubilee Line
If you wish y
Hi,
In Spark programing I can use
df.filter(col("transactiontype") ===
"DEB").groupBy("transactiondate").agg(sum("debitamount").cast("Float").as("Total
Debit Card")).orderBy("transactiondate").show(5)
or
df.filter(col("transactiontype") ===
"DEB").groupBy("transactiondate").agg(sum("debitamount"
Hi,
in the following Window spec I want orderBy ("") to be displayed in
descending order please
val W = Window.partitionBy("col1").orderBy("col2")
If I Do
val W = Window.partitionBy("col1").orderBy("col2".desc)
It throws error
console>:26: error: value desc is not a member of String
How can I ac
Hi
I would like to know the exact definition for these three parameters
num-executors
executor-memory
executor-cores
for local, standalone and yarn modes
I have looked at on-line doc but not convinced if I understand them correct.
Thanking you
Hi Gurus,
I have few large tables in rdbms (ours is Oracle). We want to access these
tables through Spark JDBC
What is the quickest way of getting data into Spark Dataframe say multiple
connections from Spark
thanking you
ll in
no case be liable for any monetary damages arising from suchloss, damage or
destruction.
On 14 August 2016 at 20:50, Ashok Kumar wrote:
Hi Gurus,
I have few large tables in rdbms (ours is Oracle). We want to access these
tables through Spark JDBC
What is the quickest way of getting data
m
Disclaimer: Use it at your own risk. Any and all responsibility for any loss,
damage or destructionof data or any other property which may arise from relying
on this email's technical content is explicitly disclaimed.The author will in
no case be liable for any monetary damages arising f
Hi,
for small to medium size clusters I think Spark Standalone mode is a good
choice.
We are contemplating moving to Yarn as our cluster grows.
What are the pros and cons of using either please. Which one offers the best
Thanking you
Gurus,
I am trying to run some examples given under directory examples
spark/examples/src/main/scala/org/apache/spark/examples/
I am trying to run HdfsTest.scala
However, when I run HdfsTest.scala against spark shell it comes back with error
Spark context available as sc.
SQL context available a
Gurus,
What are the main differences between a Resilient Distributed Data (RDD) and
Data Frame (DF)
Where one can use RDD without transforming it to DF?
Regards and obliged
Hi,
If I define a class in Scala like
case class(col1: String, col2:Int,...)
and it is created how would I be able to see its description anytime
Thanks
Hi,
class body thanks
On Friday, 19 February 2016, 11:23, Ted Yu wrote:
Can you clarify your question ?
Did you mean the body of your class ?
On Feb 19, 2016, at 4:43 AM, Ashok Kumar wrote:
Hi,
If I define a class in Scala like
case class(col1: String, col2:Int,...)
and it is
Hi,
I downloaded the zipped csv libraries from databricks/spark-csv
| |
| | | | | | | |
| databricks/spark-csvspark-csv - CSV data source for Spark SQL and DataFrames |
| |
| View on github.com | Preview by Yahoo |
| |
| |
Now I have a directory created called spark-csv-master
http://spark.apache.org/docs/latest/submitting-applications.html useful.
On Fri, Feb 19, 2016 at 7:26 AM, Ashok Kumar
wrote:
Hi,
I downloaded the zipped csv libraries from databricks/spark-csv
| |
| | | | | | | |
| databricks/spark-csvspark-csv - CSV data source for Spark SQL and
Gurus,
Is there anything like explain in Spark to see the execution plan in functional
programming?
warm regards
' )""")
table("partitionedParquet").explain(true)
On Wed, Feb 24, 2016 at 1:16 AM, Ashok Kumar
wrote:
Gurus,
Is there anything like explain in Spark to see the execution plan in functional
programming?
warm regards
Hi,
I would like to do the following
select count(*) from where column1 in (1,5))
I define
scala> var t = HiveContext.table("table")
This workst.filter($"column1" ===1)
How can I expand this to have column1 for both 1 and 5 please?
thanks
Hi,
What is the equivalent of this in Spark please
select * from mytable where column1 in (select max(column1) from mytable)
Thanks
Hi,
How can I make that work?
val d = HiveContext.table("table")
select * from table where ID = MAX(ID) from table
Thanks
Hi,
Spark doco says
Spark’s primary abstraction is a distributed collection of items called a
Resilient Distributed Dataset (RDD). RDDs can be created from Hadoop
InputFormats (such as HDFS files) or by transforming other RDDs
example:
val textFile = sc.textFile("README.md")
my question is when
Hello,
I like to be able to solve this using arrays.
I have two dimensional array of (String,Int) with 5 entries say arr("A",20),
arr("B",13), arr("C", 18), arr("D",10), arr("E",19)
I like to write a small code to order these in the order of highest Int column
so I will have arr("A",20), arr("E
gisterTempTable("test")
scala> val df = sql("SELECT struct(id, b, a) from test order by b")df:
org.apache.spark.sql.DataFrame = [struct(id, b, a): struct]
scala> df.show++|struct(id, b, a)|+----+|
[2,foo,a]|| [1,test,b]|+--
no particular reason. just wanted to know if there was another way as well.
thanks
On Saturday, 27 February 2016, 22:12, Yin Yang wrote:
Is there particular reason you cannot use temporary table ?
Thanks
On Sat, Feb 27, 2016 at 10:59 AM, Ashok Kumar wrote:
Thank you sir.
Can one do
Hi Gurus,
Appreciate if you recommend me a good book on Spark or documentation for
beginner to moderate knowledge
I very much like to skill myself on transformation and action methods.
FYI, I have already looked at examples on net. However, some of them not clear
at least to me.
Warmest regards
Thank you all for valuable advice. Much appreciated
Best
On Sunday, 28 February 2016, 21:48, Ashok Kumar
wrote:
Hi Gurus,
Appreciate if you recommend me a good book on Spark or documentation for
beginner to moderate knowledge
I very much like to skill myself on transformation and
Hi,
I have this
val weights = Array(("a", 3), ("b", 2), ("c", 5), ("d", 1), ("e", 9), ("f", 4),
("g", 6))
weights.toDF("weights","value")
I want to convert the Array to DF but I get thisor
weights: Array[(String, Int)] = Array((a,3), (b,2), (c,5), (d,1), (e,9), (f,4),
(g,6))
:33: error: value to
quot;)).collect.foreach(println)
Please why Array did not work?
On Tuesday, 1 March 2016, 8:51, Jeff Zhang wrote:
Change Array to Seq and import sqlContext.implicits._
On Tue, Mar 1, 2016 at 4:38 PM, Ashok Kumar
wrote:
Hi,
I have this
val weights = Array(("a", 3), ("b"
On Tuesday, 1 March 2016, 20:52, Shixiong(Ryan) Zhu
wrote:
For Array, you need to all `toSeq` at first. Scala can convert Array to
ArrayOps automatically. However, it's not a `Seq` and you need to call `toSeq`
explicitly.
On Tue, Mar 1, 2016 at 1:02 AM, Ashok Kumar
wrote:
Thank y
Hi,
I am new to Spark.
I am trying to use spark-sql with SPARK CREATED and HIVE CREATED tables.
I have successfully made Hive metastore to be used by Spark.
In spark-sql I can see the DDL for Hive tables. However, when I do select
count(1) from HIVE_TABLE it always returns zero rows.
If I create
Hi,
I am new to Spark.
I am trying to use spark-sql with SPARK CREATED and HIVE CREATED tables.
I have successfully made Hive metastore to be used by Spark.
In spark-sql I can see the DDL for Hive tables. However, when I do select
count(1) from HIVE_TABLE it always returns zero rows.
If I creat
This is great news sir. It shows perseverance pays at last.
Can you inform us when the write-up is ready so I can set it up as well please.
I know a bit about the advantages of having Hive using Spark engine. However,
the general question I have is when one should use Hive on spark as opposed to
Hi,
There are design patterns that use Spark extensively. I am new to this area so
I would appreciate if someone explains where Spark fits in especially within
faster or streaming use case.
What are the best practices involving Spark. Is it always best to deploy it for
processing engine,
For ex
Hi,
What are practical differences between the new Data set in Spark 2 and the
existing DataFrame.
Has Dataset replaced Data Frame and what advantages it has if I use Data Frame
instead of Data Frame.
Thanks
Hi,
I have a text file as below that I read in
74,20160905-133143,98.1121806912882759414875,20160905-133143,49.5277699881591680774276,20160905-133143,56.0802995712398098455677,20160905-133143,46.636895265444075228,20160905-133143,84.8822714116440218155179,20160905-133143,68.72408602520662115000
sformations like
map.sc.textFile("filename").map(x => x.split(",")
On 5 Sep 2016 6:19 pm, "Ashok Kumar" wrote:
Hi,
I have a text file as below that I read in
74,20160905-133143,98. 1121806912882759414875,20160905-133143,49.
5277699881591680774276,20160905-133
RDD of arrays. What
is your expected outcome of 2nd map?
On Mon, Sep 5, 2016 at 11:30 PM, Ashok Kumar
wrote:
Thank you sir.
This is what I get
scala> textFile.map(x=> x.split(","))res52: org.apache.spark.rdd.RDD[
Array[String]] = MapPartitionsRDD[27] at map at :27
How can I
t it to your desired
data type and then use filter.
On Tue, Sep 6, 2016 at 12:14 AM, Ashok Kumar wrote:
Hi,I want to filter them for values.
This is what is in array
74,20160905-133143,98. 11218069128827594148
I want to filter anything > 50.0 in the third column
Thanks
On Monday, 5 Septe
Hello Gurus,
I am creating some figures and feed them into Kafka and then spark streaming.
It works OK but I have the following issue.
For now as a test I sent 5 prices in each batch interval. In the loop code this
is what is hapening
dstream.foreachRDD { rdd => val x= rdd.count
i +
Any help on this warmly appreciated.
On Tuesday, 6 September 2016, 21:31, Ashok Kumar
wrote:
Hello Gurus,
I am creating some figures and feed them into Kafka and then spark streaming.
It works OK but I have the following issue.
For now as a test I sent 5 prices in each batch interval
Hi,
A bit confusing to me
How many layers involved in DStream.foreachRDD.
Do I need to loop over it more than once? I mean DStream.foreachRDD{ rdd = > }
I am trying to get individual lines in RDD.
Thanks
mages arising from suchloss, damage or
destruction.
On 7 September 2016 at 11:39, Ashok Kumar wrote:
Hi,
A bit confusing to me
How many layers involved in DStream.foreachRDD.
Do I need to loop over it more than once? I mean DStream.foreachRDD{ rdd = > }
I am trying to get individual lines in RDD.
Thanks
Hi,
As a learner I appreciate if you have typical Spark interview questions for
Spark/Scala junior roles that you can please forward to me.
I will be very obliged
Can one design a fast pipeline with Kafka, Spark streaming and Hbase or
something similar?
On Friday, 30 September 2016, 17:17, Mich Talebzadeh
wrote:
I have designed this prototype for a risk business. Here I would like to
discuss issues with batch layer. Apologies about being lo
What are the pros and cons of using different persistence layers for Spark,
such as S3,Cassandra, and HDFS?
Thanks
You are very kind Sir
On Sunday, 30 October 2016, 16:42, Devopam Mittra wrote:
+1
Thanks and regards
Devopam
On 30 Oct 2016 9:37 pm, "Mich Talebzadeh" wrote:
Enjoy the festive season.
Regards,
Dr Mich Talebzadeh LinkedIn https://www.linkedin.com/ profile/view?id=
AAEWh2gBxianrbJd
Hello,
What are the practiced High Availability/DR operations for Spark cluster at the
moment. I am specially interested if YARN is used as the resource manager.
Thanks
llow me at https://twitter.com/jaceklaskowski
On Sun, Feb 5, 2017 at 10:11 AM, Ashok Kumar
wrote:
> Hello,
>
> What are the practiced High Availability/DR operations for Spark cluster at
> the moment. I am specially interested if YARN is
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