Re: Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

What about this configure in Yarn "yarn.scheduler.maximum-allocation-mb" I'm curious why 49 executors can be worked, but 50 failed. Would you provide your application master log, if container request is issued, there will be log like: 15/10/14 17:35:37 INFO yarn.YarnAllocator: Will request 2 exec

Re: Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

OK, the YARN conf will be list in the following: yarn.nodemanager.resource.memory-mb:115200 yarn.nodemanager.resource.cpu-vcores:50 I think the YARN resource is sufficient. In the previous letter I have said that I think Spark application didn't request resources from YARN. Thanks 2015-11-24 1

Re: DateTime Support - Hive Parquet

Hey Bryan, What do you mean by "DateTime properties"? Hive and Spark SQL both support DATE and TIMESTAMP types, but there's no DATETIME type. So I assume you are referring to Java class DateTime (possibly the one in joda)? Could you please provide a sample snippet that illustrates your requir

Re: Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

can you show your parameter values in your env ? yarn.nodemanager.resource.cpu-vcores yarn.nodemanager.resource.memory-mb cherrywayb...@gmail.com From: 谢廷稳 Date: 2015-11-24 12:13 To: Saisai Shao CC: spark users Subject: Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloct

Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

Hi Saisai, Would you mind giving me some tips about this problem? After check YARN RM logs, I think Spark application didn't request resources from it, So, I guess this problem is none of YARN's business. and the spark conf of my cluster will be list in the following: spark.shuffle.service.enabled

Re: Spark Kafka Direct Error

Does Kafka direct query the offsets from the zookeeper directly? From where does it get the offsets? There is data in those offsets, but somehow Kafka Direct does not seem to pick it up. Other Consumers that use Zoo Keeper Quorum of that Stream seems to be fine. Only Kafka Direct seems to have issu

Re: load multiple directory using dataframe load

hiveContext.read.format(“orc”).load(“bypath/*”) > On Nov 24, 2015, at 1:07 PM, Renu Yadav wrote: > > Hi , > > I am using dataframe and want to load orc file using multiple directory > like this: > hiveContext.read.format.load("mypath/3660,myPath/3661") > > but it is not working. > > Please

Re: Spark Streaming idempotent writes to HDFS

Not sure if it would be the most efficient, but maybe you can think of the filesystem as a key value store, and write each batch to a sub-directory, where the directory name is the batch time. If the directory already exists, then you shouldn't write it. Then you may have a following batch job that

Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

I don't think it is a bug, maybe something wrong with your Spark / Yarn configurations. On Tue, Nov 24, 2015 at 12:13 PM, 谢廷稳 wrote: > OK,the YARN cluster was used by myself,it have 6 node witch can run over > 100 executor, and the YARN RM logs showed that the Spark application did > not request

load multiple directory using dataframe load

Hi , I am using dataframe and want to load orc file using multiple directory like this: hiveContext.read.format.load("mypath/3660,myPath/3661") but it is not working. Please suggest how to achieve this Thanks & Regards, Renu Yadav

Spark Streaming idempotent writes to HDFS

Hi all, I'm working on project with spark streaming, the goal is to process log files from S3 and save them on hadoop to later analyze them with sparkSQL. Everything works well except when I kill the spark application and restart it: it picks up from the latest processed batch and reprocesses it

Re: How to have Kafka Direct Consumers show up in Kafka Consumer reporting?

OK. I see the following to query the offsets. In our Kafka Stream, the offsets are stored in ZooKeeper and I am not updating Offsets in Zookeeper. How does Kafka Direct know which offsets to query? Does it calculate automatically as to which offsets to query?I have "auto.offset.reset" -> "largest

Re: Relation between RDDs, DataFrames and Project Tungsten

> > In the near future, I guess GUI interfaces of Spark will be available > soon. Spark users (e.g, CEOs) might not need to know what are RDDs at all. > They can analyze their data by clicking a few buttons, instead of writing > the programs. : ) That's not in the future. :) On Mon, Nov 23, 201

Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

OK,the YARN cluster was used by myself,it have 6 node witch can run over 100 executor, and the YARN RM logs showed that the Spark application did not requested resource from it. Is this a bug? Should I create a JIRA for this problem? 2015-11-24 12:00 GMT+08:00 Saisai Shao : > OK, so this looks l

Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

OK, so this looks like your Yarn cluster does not allocate containers which you supposed should be 50. Does the yarn cluster have enough resource after allocating AM container, if not, that is the problem. The problem not lies in dynamic allocation from my guess of your description. I said I'm OK

Re: newbie : why are thousands of empty files being created on HDFS?

Hi Andy You can try sc.wholeTextFiles() instead of sc.textFile() Regards Sab On 24-Nov-2015 4:01 am, "Andy Davidson" wrote: > Hi Xiao and Sabarish > > Using the Stage tab on the UI. It turns out you can see how many > partitions there are. If I did nothing I would have 228155 partition. > (This

Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

Hi Saisai, I'm sorry for did not describe it clearly,YARN debug log said I have 50 executors,but ResourceManager showed that I only have 1 container for the AppMaster. I have checked YARN RM logs,after AppMaster changed state from ACCEPTED to RUNNING,it did not have log about this job any more.So,

Re: Relation between RDDs, DataFrames and Project Tungsten

Let me share my understanding. If we view Spark as analytics OS, RDD APIs are like OS system calls. These low-level system calls can be called in the program languages like C. DataFrame and Dataset APIs are like higher-level programming languages. They hide the low level complexity and the compile

Re: newbie : why are thousands of empty files being created on HDFS?

I'm seeing similar slowness in saveAsTextFile(), but only in Python. I'm sorting data in a dataframe, then transform it and get a RDD, and then coalesce(1).saveAsTextFile(). I converted the Python to Scala and the run-times were similar, except for the saveAsTextFile() stage. The scala version w

Re: Port Control for YARN-Aware Spark

On Mon, Nov 23, 2015 at 6:24 PM, gpriestley wrote: > Questions I have are: > 1) How does the spark.yarn.am.port relate to defined ports within Spark > (driver, executor, block manager, etc.)? > 2) Doe the spark.yarn.am.port parameter only relate to the spark > driver.port? > 3) Is the spark.yarn.a

Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

I think this behavior is expected, since you already have 50 executors launched, so no need to acquire additional executors. You change is not solid, it is just hiding the log. Again I think you should check the logs of Yarn and Spark to see if executors are started correctly. Why resource is stil

Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

Hi SaiSai, I have changed "if (numExecutorsTarget >= maxNumExecutors)" to "if (numExecutorsTarget > maxNumExecutors)" of the first line in the ExecutorAllocationManager#addExecutors() and it rans well. In my opinion,when I was set minExecutors equals maxExecutors,when the first time to add Execut

Apache Cassandra Docker Images?

Hello, any planned support for official Docker images? Would be great having some images using the cluster manager of choice (Standalone, Yarn, Mesos) with the latest Apache Spark distribution (ideally, using CentOS 7.x) for clusterizable containers. Regards, Renato Perini. --

Re: spark-ec2 script to launch cluster running Spark 1.5.2 built with HIVE?

Don't the Hadoop builds include Hive already? Like spark-1.5.2-bin-hadoop2.6.tgz? On Mon, Nov 23, 2015 at 7:49 PM Jeff Schecter wrote: > Hi all, > > As far as I can tell, the bundled spark-ec2 script provides no way to > launch a cluster running Spark 1.5.2 pre-built with HIVE. > > That is to sa

Re: How to have Kafka Direct Consumers show up in Kafka Consumer reporting?

Also, does Kafka direct query the offsets from the zookeeper directly? From where does it get the offsets? There is data in those offsets, but somehow Kafka Direct does not seem to pick it up? On Mon, Nov 23, 2015 at 6:18 PM, swetha kasireddy wrote: > I mean to show the Spark Kafka Direct consum

Port Control for YARN-Aware Spark

Hello Community, I have what I hope to be a couple of quick questions regarding port control on Spark which is Yarn-aware (cluster & client modes). I'm aware that I can control port configurations by setting driver.port, executor.port, etc to use specified ports, but I'm not sure how/if that cor

Re: How to have Kafka Direct Consumers show up in Kafka Consumer reporting?

I mean to show the Spark Kafka Direct consumers in Kafka Stream UI. Usually we create a consumer and the consumer gets shown in the Kafka Stream UI. How do I log the offsets in the Spark Job? On Mon, Nov 23, 2015 at 6:11 PM, Cody Koeninger wrote: > What exactly do you mean by kafka consumer repo

Re: How to have Kafka Direct Consumers show up in Kafka Consumer reporting?

What exactly do you mean by kafka consumer reporting? I'd log the offsets in your spark job and try running kafka-simple-consumer-shell.sh --partition $yourbadpartition --print-offsets at the same time your spark job is running On Mon, Nov 23, 2015 at 7:37 PM, swetha wrote: > Hi, > > We see a

Re: Any workaround for Kafka couldn't find leaders for set?

If you really want to just not process the bad topicpartitions, you can use the version of createDirectStream that takes fromOffsets: Map[TopicAndPartition, Long] and exclude the broken topicpartitions from the map. On Mon, Nov 23, 2015 at 4:54 PM, Hudong Wang wrote: > Hi folks, > > We have a

Re: Relation between RDDs, DataFrames and Project Tungsten

Thanks Michael, that helped me a lot! On 23 November 2015 at 17:47, Michael Armbrust wrote: > Here is how I view the relationship between the various components of > Spark: > > - *RDDs - *a low level API for expressing DAGs that will be executed in > parallel by Spark workers > - *Catalyst -*

Re: Relation between RDDs, DataFrames and Project Tungsten

Here is how I view the relationship between the various components of Spark: - *RDDs - *a low level API for expressing DAGs that will be executed in parallel by Spark workers - *Catalyst -* an internal library for expressing trees that we use to build relational algebra and expression evaluation

How to have Kafka Direct Consumers show up in Kafka Consumer reporting?

Hi, We see a bunch of issues like the following in Our Spark Kafka Direct. Any idea as to how make Kafka Direct Consumers show up in Kafka Consumer reporting to debug this issue? Job aborted due to stage failure: Task 47 in stage 336.0 failed 4 times, most recent failure: Lost task 47.3 in stag

Re: Dataframe constructor

just simple as: val df = sqlContext.sql(“select * from table”) or val df = sqlContext.read.json(“hdfs_path”) > On Nov 24, 2015, at 3:09 AM, spark_user_2015 wrote: > > Dear all, > > is the following usage of the Dataframe constructor correct or does it > trigger any side effects that I shou

spark-ec2 script to launch cluster running Spark 1.5.2 built with HIVE?

Hi all, As far as I can tell, the bundled spark-ec2 script provides no way to launch a cluster running Spark 1.5.2 pre-built with HIVE. That is to say, all of the pre-build versions of Spark 1.5.2 in the s3 bin spark-related-packages are missing HIVE. aws s3 ls s3://spark-related-packages/ | gre

Relation between RDDs, DataFrames and Project Tungsten

Hi everyone, I'm doing some reading-up on all the newer features of Spark such as DataFrames, DataSets and Project Tungsten. This got me a bit confused on the relation between all these concepts. When starting to learn Spark, I read a book and the original paper on RDDs, this lead me to basically

Any workaround for Kafka couldn't find leaders for set?

Hi folks, We have a 10 node cluster and have several topics. Each topic has about 256 partitions with 3 replica factor. Now we run into an issue that in some topic, a few partition (< 10)'s leader is -1 and all of them has only one synced partition. Exception in thread "main" org.apache.spark.Sp

Re: newbie : why are thousands of empty files being created on HDFS?

Hi Xiao and Sabarish Using the Stage tab on the UI. It turns out you can see how many partitions there are. If I did nothing I would have 228155 partition. (This confirms what Sabarish said). I tried coalesce(3). RDD.count() fails. I though given I have 3 workers and 1/3 of the data would easily f

Add Data Science Serbia meetup

Please add Data Science Serbia meetup group to list on the web site. http://www.meetup.com/Data-Science-Serbia/ Thank you. Best, Darko Marjanovic CEO & Co-Founder Things Solver *M: +381637052054* *E: da...@thingsolver.com *

Re: how to us DataFrame.na.fill based on condition

You could create a new column based on the expression: IF (condition1, value1, old_column_value) On Mon, Nov 23, 2015 at 11:57 AM, Vishnu Viswanath wrote: > Thanks for the reply Davies > > I think replace, replaces a value with another value. But what I want to do > is fill in the null value of a

Re: Need Help Diagnosing/operating/tuning

you should check why executor is killed. as soon as it's killed you can get all kind of strange exceptions... either give your executors more memory(4G is rather small for spark ) or try to decrease your input or maybe split it into more partitions in input format 23G in lzo might expand to x?

Re: newbie : why are thousands of empty files being created on HDFS?

In your case, maybe you can try to call the function coalesce? Good luck, Xiao Li 2015-11-23 12:15 GMT-08:00 Andy Davidson : > Hi Sabarish > > I am but a simple padawan :-) I do not understand your answer. Why would > Spark be creating so many empty partitions? My real problem is my > applicati

spark-csv on Amazon EMR

Hi, Some know how to use spark-csv in create-cluster statement of Amazon EMR CLI? Best, -- *Daniel Lopes, B.Eng* Data Scientist - BankFacil CREA/SP 5069410560 Mob +55 (18) 99764-2733 Ph +55 (11) 3522-8009 http://abou

Re: newbie : why are thousands of empty files being created on HDFS?

Hi Sabarish I am but a simple padawan :-) I do not understand your answer. Why would Spark be creating so many empty partitions? My real problem is my application is very slow. I happened to notice thousands of empty files being created. I thought this is a hint to why my app is slow. My program

Re: how to us DataFrame.na.fill based on condition

Thanks for the reply Davies I think replace, replaces a value with another value. But what I want to do is fill in the null value of a column.( I don't have a to_replace here ) Regards, Vishnu On Mon, Nov 23, 2015 at 1:37 PM, Davies Liu wrote: > DataFrame.replace(to_replace, value, subset=None

Re: how to us DataFrame.na.fill based on condition

DataFrame.replace(to_replace, value, subset=None) http://spark.apache.org/docs/latest/api/python/pyspark.sql.html#pyspark.sql.DataFrame.replace On Mon, Nov 23, 2015 at 11:05 AM, Vishnu Viswanath wrote: > Hi > > Can someone tell me if there is a way I can use the fill method in > DataFrameNaFunct

how to us DataFrame.na.fill based on condition

Hi Can someone tell me if there is a way I can use the fill method in DataFrameNaFunctions based on some condition. e.g., df.na.fill("value1","column1","condition1") df.na.fill("value2","column1","condition2") i want to fill nulls in column1 with values - either value 1 or value 2, based

Dataframe constructor

Dear all, is the following usage of the Dataframe constructor correct or does it trigger any side effects that I should be aware of? My goal is to keep track of my dataframe's state and allow custom transformations accordingly. val df: Dataframe = ...some dataframe... val newDf = new DF(df.s

Re: Spark Kafka Direct Error

No, that means that at the time the batch was scheduled, the kafka leader reported the ending offset was 221572238, but during processing, kafka stopped returning messages before reaching that ending offset. That probably means something got screwed up with Kafka - e.g. you lost a leader and lost

Spark Kafka Direct Error

Hi, I see the following error in my Spark Kafka Direct. Would this mean that Kafka Direct is not able to catch up with the messages and is failing? Job aborted due to stage failure: Task 20 in stage 117.0 failed 4 times, most recent failure: Lost task 20.3 in stage 117.0 (TID 2114, 10.227.64.52):

Re: Please add us to the Powered by Spark page

Sorry to be a nag, I realize folks with edit rights on the Powered by Spark page are very busy people, but its been 10 days since my original request, was wondering if maybe it just fell through the cracks. If I should submit via some other channel that will make sure it is looked at (or better yet

Getting different DESCRIBE results between SparkSQL and Hive

Example below. The partition columns show up as regular columns. I'll note that SHOW PARTITIONS works correctly in Spark SQL, so it's aware of the partitions but it does not show them in DESCRIBE. In Hive: "DESCRIBE pub.inventory_daily" [['effective_dat

spark 1.4.1 to oracle 11g write to an existing table

Hi, I am trying to write a dataframe from Spark 1.4.1 to oracle 11g I am using dataframe.write.mode(SaveMode.Append).jdbc(url,tablename, properties) this is always trying to create a Table. I would like to insert records to an existing table instead of creating a new one each single time. Plea

A question about sql clustering

Let's assume that I have a code like the following: val sqlQuery = "select * from whse.table_a cluster by user_id" val df = hc.sql(sqlQuery) My understanding is that the cluster function will partition the data frame by user_id and also sort inside each partition (something very useful for perfor

Re: RDD partition after calling mapToPair

Partitioner is an optional field when defining an rdd. KafkaRDD doesn't define one, so you can't really assume anything about the way it's partitioned, because spark doesn't know anything about the way it's partitioned. If you want to rely on some property of how things were partitioned as they w

Re: RDD partition after calling mapToPair

Thanks Cody, I still have concerns about this. What's do you mean by saying Spark direct stream doesn't have a default partitioner? Could you please help me to explain more? When i assign 20 cores to 20 Kafka partitions, I am expecting each core will work on a partition. Is it correct? I'm still

Re: Re: RE: Error not found value sqlContext

Thanks for all the support. It was a code issue which I overlooked it Regards, Satish Chandra On Mon, Nov 23, 2015 at 3:49 PM, satish chandra j wrote: > Sorry, just to understand my issue.if Eclipse could not understand > Scala syntax properly than it should error for the other Spark Job wh

DateTime Support - Hive Parquet

All, I am attempting to write objects that include a DateTime properties to a persistent table using Spark 1.5.2 / HiveContext. In 1.4.1 I was forced to convert the DateTime properties to Timestamp properties. I was under the impression that this issue was fixed in the default Hive supported wit

Re: Data in one partition after reduceByKey

I will answer my own question, since I figured it out. Here is my answer in case anyone else has the same issue. My DateTimes were all without seconds and milliseconds since I wanted to group data belonging to the same minute. The hashCode() for Joda DateTimes which are one minute apart is a cons

Re: A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

Hi Tingwen, Would you minding sharing your changes in ExecutorAllocationManager#addExecutors(). >From my understanding and test, dynamic allocation can be worked when you set the min to max number of executors to the same number. Please check your Spark and Yarn log to make sure the executors ar

A Problem About Running Spark 1.5 on YARN with Dynamic Alloction

Hi all, I ran a SparkPi on YARN with Dynamic Allocation enabled and set spark.dynamicAllocation.maxExecutors equals spark.dynamicAllocation.minExecutors,then I submit an application using: ./bin/spark-submit --class org.apache.spark.examples.SparkPi --master yarn-cluster --driver-memory 4g --exec

Re: Re: RE: Error not found value sqlContext

Sorry, just to understand my issue.if Eclipse could not understand Scala syntax properly than it should error for the other Spark Job which is fetching data from a RDBM and printing the output in console. I think there is some dependencies which are missing due to which "import sqlContext.impli

Re: SparkR DataFrame , Out of memory exception for very small file.

>>> names(SALES)[which(names(SALES)=="div_no")]<-"DIV_NO" This line only create a new data frame. The memory overhead is only the new dataframe object itself, not including its data. So it would be a very little memory consumption. Which line cause the OOM in your case ? On Mon, Nov 23, 2015 a

Re:Re: RE: Error not found value sqlContext

So it is actually a compile time error in Eclipse, instead of jar generation from Eclipse, you can try to use sbt to assembly your jar, looks like your Eclipse does not recognize the Scala syntax properly. At 2015-11-20 21:36:55, "satish chandra j" wrote: HI All, I am getting this error wh

Re: SparkR DataFrame , Out of memory exception for very small file.

Hi Jeff, This is only part of the actual code. My questions are mentioned in comments near the code. SALES<- SparkR::sql(hiveContext, "select * from sales") PRICING<- SparkR::sql(hiveContext, "select * from pricing") ## renaming of columns ## #sales file# # Is this right ??? Do we have to cre

Re: how to use sc.hadoopConfiguration from pyspark

2015-11-23 10:26 GMT+01:00 Tamas Szuromi : > Hello Eike, > > Thanks! Yes I'm using it with Hadoop 2.6 so I'll give a try to the 2.4 > build. > Have you tried it with 1.6 Snapshot or do you know JIRA tickets for this > missing libraries issues? I've not tried 1.6. https://issues.apache.org/jira/br

Re: how to use sc.hadoopConfiguration from pyspark

Hello Eike, Thanks! Yes I'm using it with Hadoop 2.6 so I'll give a try to the 2.4 build. Have you tried it with 1.6 Snapshot or do you know JIRA tickets for this missing libraries issues? Tamas On 23 November 2015 at 10:21, Eike von Seggern wrote: > Hello Tamas, > > 2015-11-20 17:23 GMT+0

Re: SparkR DataFrame , Out of memory exception for very small file.

If possible, could you share your code ? What kind of operation are you doing on the dataframe ? On Mon, Nov 23, 2015 at 5:10 PM, Vipul Rai wrote: > Hi Zeff, > > Thanks for the reply, but could you tell me why is it taking so much time. > What could be wrong , also when I remove the DataFrame fr

Re: how to use sc.hadoopConfiguration from pyspark

Hello Tamas, 2015-11-20 17:23 GMT+01:00 Tamas Szuromi : > > Hello, > > I've just wanted to use sc._jsc.hadoopConfiguration().set('key','value') in > pyspark 1.5.2 but I got set method not exists error. For me it's working with Spark 1.5.2 binary distribution built against Hadoop 2.4 (spark-1.5.

Re: SparkR DataFrame , Out of memory exception for very small file.

Hi Zeff, Thanks for the reply, but could you tell me why is it taking so much time. What could be wrong , also when I remove the DataFrame from memory using rm(). It does not clear the memory but the object is deleted. Also , What about the R functions which are not supported in SparkR. Like ddpl

Re: SparkR DataFrame , Out of memory exception for very small file.

>>> Do I need to create a new DataFrame for every update to the DataFrame like addition of new column or need to update the original sales DataFrame. Yes, DataFrame is immutable, and every mutation of DataFrame will produce a new DataFrame. On Mon, Nov 23, 2015 at 4:44 PM, Vipul Rai wrote: >

Re: SparkR DataFrame , Out of memory exception for very small file.

Hello Rui, Sorry , What I meant was the resultant of the original dataframe to which a new column was added gives a new DataFrame. Please check this for more https://spark.apache.org/docs/1.5.1/api/R/index.html Check for WithColumn Thanks, Vipul On 23 November 2015 at 12:42, Sun, Rui wrote