Skip to main content

Learning Spark Streaming #1

I have been doing a lot of Spark in the past few months, and of late, have taken a keen interest in Spark Streaming. In a series of posts, I intend to cover a lot of details about Spark streaming and even other stream processing systems in general, either presenting technical arguments/critiques, with any micro benchmarks as needed.

Some high level description of Spark Streaming (as of 1.4),  most of which you can find in the programming guide.  At a high level, Spark streaming is simply a spark job run on very small increments of input data (i.e micro batch), every 't' seconds, where t can be as low as 1 second.

As with any stream processing system, there are three big aspects to the framework itself.

  1. Ingesting the data streams : This is accomplished via DStreams, which you can think of effectively as a thin wrapper around an input source such as Kafka/HDFS which knows how to read the next N entries from the input.
    • The receiver based approach is a little complicated IMHO, and my recommendation is to avoid that route completely, since for the most part, it should be possible to refetch the data from the input source such as Kafka/HDFS

  2. Computing the result : Once new input is available, typically you execute the Spark DAG (which is basically your streaming job), computing your final result and optionally outputting that to a serving store such as a NoSQL datastore periodically. 
  3. Updating the internal state : Along the way during DAG execution, you would frequently need access to the results from previous computations, that you want to 'update'  based on new input. For e.g.: if you were tracking the page views in the last hour, then you need to increment some counters based on the last 't' second of data. Spark Streaming currently implements this via the StateDStream/StateRDD, which is basically like any other normal Spark RDD. 

Some good things about this model : (the paper is still a better source)

  1. Spark Streaming computes the entire computation once, for each micro batch. Thus, there are very clear semantics of what the result means, whereas in a per-event model (such as Storm/Samza) different input/output/intermediate streams can be in different points in time. 
  2. Once you read data off your input stream, you are no longer bound by the number of partitions in say your Kafka stream. You can repartition your data as you like, and let Spark & in-memory glory take over. 

So, what could be bad? (sticking to design level problems only)
  • Given the tight coupling between different computations in the DAG, if a single stage in the DAG were to be slow, you could end up with back pressure issues. (Good news inside bad news is, since next batches cannot be scheduled, it self throttles)
  • RDDs are built for immutability, reusing the same constructs for internal state maintenance, can be very inefficient
  • The common criticism is that its not pure streaming, but simply "micro batch" alluding to increased latency, when you compare to something like Storm. (My take on this is, if you want sub-second latency, then your service must be talking to a database i.e state store directly to begin with). But its a fair point and remains to be seen in what shape/form this truly impacts practical applications.

Let's take baby steps, towards understanding how Spark Streaming works under the hoods, by writing our very own CountingDStream, which does one simple thing, keeps counting. We will evolve this as we go to understand aspects like Checkpointing, State management, Recovery, Caching and so on.

Its actually very straightforward. First we implement the InputDStream trait/interface. The meat is in the compute() method, which is tasked to return the next set of inputs as an RDD every micro batch.

Now, the driver program that runs this and just prints out the counters. (Exercise: Increase the number of partitions to parallelize(..) from 1, to observe the effect on the counts printed out)

Next, lets add checkpoints to this DStream, so we will be able to kill and resume our counting..


  1. How does Spark Streaming know to fetch the entire record from the stream? Is it possible for micro batch to have partial record (the last record can be incomplete)?

    1. IEEE Final Year projects Project Center in Chennai are consistently sought after. Final Year Students Projects take a shot at them to improve their aptitudes. Final Year Project Domains for IT

      JavaScript Training in Chennai

      JavaScript Training in Chennai

      The Angular Training covers a wide range of topics including Components, project projects for cse. Angular Training

  2. Thanks for sharing, nice post!

    Chia sẻ các bạn về bệnh thủy đậu với blog hay bà bầu uống thuốc thì nên lưu ý với blog hay để đảm bảo giấc ngủ cho trẻ em các mẹ tham khảo blog hay bệnh thủy đậu lưu ý kiêng cử gì với bài người bị bệnh thủy đậu nên ăn gì hay trẻ em nhiệt miệng kiêng ko ăn gì với bài trẻ bị nhiệt miệng nên ăn gì hay những ai làm món kim chi hàn quốc thì tham khảo bài ớt bột hàn quốc mua ở đâu giá bao nhiêu hay bột ca cao giá bao nhiêu bột ca cao có tác dụng gì, bột ca cao mua ở đâu hay bột gelatin có bán ở siêu thị không bột gelatin mua ở đâu, bột gelatin giá bao nhiêu tinh bột nghệ có bán ở siêu thị không tinh bột nghệ có bán ở hiệu thuốc không, tinh bột nghệ giá bao nhiêu hay bột trà xanh có bán ở siêu thị không bột trà xanh matcha giá bao nhiêu hay baking soda có bán ở siêu thị không baking soda có bán ở hiệu thuốc không.

  3. Nice info regarding spark streaming My sincere thanks for sharing this post Please Continue to share this post
    Hadoop Training in Chennai

  4. nice blog has been shared by you. before i read this blog i didn't have any knowledge about this but now i got some knowledge. so keep on sharing such kind of an interesting blogs.
    hadoop training in chennai

  5. Hi, I am really happy to found such a helpful and fascinating post that is written in well manner. Thanks for sharing such an informative post..Big Data Hadoop Training in Bangalore | Data Science Training in Bangalore

  6. If you want to play like me and not lose, you should try playing BGAOC. free gambling with us Playing here you not only win but also get a lot of fun.

  7. Современная диодная лента по всем стандартам отличного качества я обычно беру у компании Ekodio

  8. I am reading your post from the beginning, it was so interesting to read & I feel thanks to you for posting such a good blog, keep updates regularly.
    Java Training in Chennai
    Java Training in Coimbatore
    Java Training in Bangalore

  9. For Hadoop Training in Bangalore Visit : Hadoop Training in Bangalore

  10. Great blog thanks for sharing Instagram and Facebook have provided an amazing place for new brands to grow and flourish. We can find the perfect niche for your brand on the best social media platforms. Marketing through social media brings forth global audience without all these physical boundaries. Analyze and take over the competition with ease with Adhuntt Media’s digital marketing tools and strategies.
    digital marketing company in chennai

  11. Nice blog thanks for sharing Buy unique easy to maintain indoor plants and exotic garden plants all at the same place - Karuna Nursery - the best nursery garden in Chennai. With our exclusive collection of plants and special deals on bulk orders - you know you are at the right place.
    plant nursery in chennai

  12. Excellent blog thanks for sharing Looking for the best place in Chennai to get your cosmetics at wholesale? The Pixies Beauty Shop is the premium wholesale cosmetics shop in Chennai that has all the international brands your salon deserves.
    beauty Shop in Chennai

  13. Great Article. Thank you for sharing! Really an awesome post for every one.

    IEEE Final Year projects Project Centers in Chennai are consistently sought after. Final Year Students Projects take a shot at them to improve their aptitudes, while specialists like the enjoyment in interfering with innovation. For experts, it's an alternate ball game through and through. Smaller than expected IEEE Final Year project centers ground for all fragments of CSE & IT engineers hoping to assemble. Final Year Project Domains for IT It gives you tips and rules that is progressively critical to consider while choosing any final year project point.

    Spring Framework has already made serious inroads as an integrated technology stack for building user-facing applications. Spring Framework Corporate TRaining the authors explore the idea of using Java in Big Data platforms.
    Specifically, Spring Framework provides various tasks are geared around preparing data for further analysis and visualization. Spring Training in Chennai

  14. You have provided a nice article, Thank you very much for this one. And I hope this will be useful for many people. And I am waiting for your next post keep on updating these kinds of knowledgeable things
    Android Training in Chennai
    Android Course in Chennai
    Android Training in Bangalore
    Android Course in Bangalore
    Android Training in Coimbatore
    Android Course in Coimbatore
    Android Training in Madurai

  15. Nice blog, it’s so knowledgeable, informative, and good looking site. I appreciate your hard work. Good job. Thank you for this wonderful sharing with us. Keep Sharing.
    Digital Marketing Course In Kolkata
    Web Design Course In Kolkata

  16. Nice blog,I understood the topic very clearly,And want to study more like this.
    Data Scientist Course

  17. Thank you for sharing this blog, it is very useful for understanding the java programming.
    Even we also provide some tutorial related to this topic. For more information visit trishana technology.

  18. Cool stuff you have and you keep overhaul every one of us

    data science course

  19. Thanks a lot for sharing such a good source with all, i appreciate your efforts taken for the same. I found this worth sharing and must share this with all.

    Dot Net Training in Chennai | Dot Net Training in anna nagar | Dot Net Training in omr | Dot Net Training in porur | Dot Net Training in tambaram | Dot Net Training in velachery

  20. I like viewing web sites which comprehend the price of delivering the excellent useful resource free of charge. I truly adored reading your posting. Thank you!

    Simple Linear Regression

    Correlation vs Covariance

  21. Amazing Article ! I would like to thank you for the efforts you had made for writing this awesome article. This article inspired me to read more. keep it up.
    Correlation vs Covariance
    Simple Linear Regression
    data science interview questions
    KNN Algorithm

  22. It is amazing and wonderful to visit your site.Thanks for sharing this information,this is useful to science courses

  23. I just loved your article on the beginners guide to starting a blog.If somebody take this blog article seriously in their life, he/she can earn his living by doing blogging.thank you for this article.

    angular js training in chennai

    angular js training in velachery

    full stack training in chennai

    full stack training in velachery

    php training in chennai

    php training in velachery

    photoshop training in chennai

    photoshop training in velachery

  24. Very nice blogs!!! i have to learning for lot of information for this sites…Sharing for wonderful information.Thanks for sharing this valuable information to our vision. You have posted a trust worthy blog keep sharing, data scientist courses

  25. Attend The Data Analyst Course From ExcelR. Practical Data Analyst Course Sessions With Assured Placement Support From Experienced Faculty. ExcelR Offers The Data Analyst Course.
    Data Analyst Course

  26. I really thank you for the valuable info on this great subject and look forward to more great posts
    data scientist training in hyderabad

  27. This was a wonderful post being shared. The entire content in this blog is extremely helpful for me and gave me a clear idea on the concepts.
    Data Science Training in Hyderabad
    Data Science Course in Hyderabad

  28. The best thing is that your blog really informative thanks for your great information!
    DevOps Training in Hyderabad
    DevOps Course in Hyderabad

  29. Hi,
    Good job & thank you very much for the new information, i learned something new. Very well written. It was SOOO good to read and use full to improve knowledge. Who want to learn this information most helpful?
    Python Training in Hyderabad
    Python Course in Hyderabad

  30. Thanks for bringing such innovative content which truly attracts the readers towards you. Certainly, your blog competes with your co-bloggers to come up with the newly updated info. Finally, kudos to you.

    Data Science Course in Varanasi

  31. Thanks for posting the best information and the blog is very good.artificial intelligence course in hyderabad

  32. Thanks for posting the best information and the blog is very science institutes in hyderabad

  33. Extremely overall quite fascinating post. I was searching for this sort of data and delighted in perusing this one. Continue posting. A debt of gratitude is in order for sharing. cloud computing course in jaipur


Post a Comment

Popular posts from this blog

Setting up Hadoop/YARN/Spark/Hive on Mac OSX El Capitan

If you are like me, who loves to have everything you are developing against working locally in a mini-integration environment, read on Here, we attempt to get some pretty heavy-weight stuff working locally on your mac, namely Hadoop (Hadoop2/HDFS) YARN (So you can submit MR jobs) Spark (We will illustrate with Spark Shell, but should work on YARN mode as well) Hive (So we can create some tables and play with it)  We will use the latest stable Cloudera distribution, and work off the jars. Most of the methodology is borrowed from here , we just link the four pieces together nicely in this blog.  Download Stuff First off all, make sure you have Java 7/8 installed, with JAVA_HOME variable setup to point to the correct location. You have to download the CDH tarballs for Hadoop, Zookeeper, Hive from the tarball page (CDH 5.4.x page ) and untar them under a folder (refered to as CDH_HOME going forward) as hadoop, zookeeper $ ls $HOME /bin/cdh/5.4.7 hadoop

HDFS Client Configs for talking to HA Hadoop NameNodes

One more simple thing, that had relatively scarce documentation out on the Internet. As you might know, Hadoop NameNodes finally became HA in 2.0 . The HDFS client configuration, which is already a little bit tedious, became more complicated. Traditionally, there were two ways to configure a HDFS client (lets stick to Java) Copy over the entire Hadoop config directory with all the xml files, place it somewhere in the classpath of your app or construct a Hadoop Configuration object by manually adding in those files. Simply provide the HDFS NameNode URI and let the client do the rest.          Configuration conf = new Configuration(false);         conf.set("", "hdfs://localhost:8020"); // this is deprecated now         conf.set("fs.defaultFS", "hdfs://localhost:8020");         FileSystem fs = FileSystem.get(conf); Most people prefer 2, unless you need way more configs from the actual xml config files, at which po