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Taming Big Data with Apache Spark and Python – Hands On!

(12 avis client)


PySpark tutorial with 20+ hands-on examples of analyzing large data sets on your desktop or on Hadoop with Python!

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12 avis pour Taming Big Data with Apache Spark and Python – Hands On!

  1. Anastasios Kotronis

    Nice course. Some code parts on Streaming don’t run. Other people had this problem as seen in the Q&A. Good slides and explanations. I would generally recommend it.

  2. Michał Gołębiewski

    tl;dr: buy if on sale and want to learn how Spark works in theory.

    starts with comprehensive intro to Spark. plenty of materials with Spark internals and architecture. it seems a little bit outdated tho; way too much RDDs and not enough SparkSQL. examples were _boring_ and not a real life scenarios, hardly being any reference for a project one could use for learning Spark. ML/Streaming hardly even talked upon, just run the code provided without any deep explanation. also, if you want to learn without any programming knowledge its definitely not for you! all in all i wouldnt really buy it again.

  3. Surya Narayanan Srinivasan

    This course on Spark is so helpful. I am a beginner in Spark. So, this course is very understandable and useful. Since, all code are written in python, I also felt comfortable understanding it. Thank you.

  4. Mike Peo

    Good level of detail while navigating through high level concepts. The examples and exercises are well constructed and very helpful. The instructor is clear and concise in his descriptions of each concept.

  5. Mark Becker

    I really liked Frank Kane’s teaching style and thought that the code examples were clear and well organized, with well defined teaching goals. I thought the course was really good up until the “advanced” Spark section, where the examples started to get away from teaching Spark SQL and the code was very down-in-the-weeds, particularly with the breadth-first search example. The movie similarity example was also getting complicated, but I appreciate that Frank needed a real world example that would involve enough scale to run on a cluster. Also the SparkML section I found unsatisfactory–I don’t think it was enough to get such poor results from the machine learning examples, without presenting some way of measuring the results (like a quick RMSE) and improving them. In general, I more time could have been spent covering the more of the large number of Spark SQL APIs. Also, it would have been good to get more understanding of how to run Spark code on a cluster, beyond fiddling with partitionBy(). But overall a good course.

  6. Carlos Andrés Campo González

    Very good class! Examples are the best way to learn anything, and the explanations are clear and succinct. Thanks.

  7. José Miguel Manzanares Chirinos

    This course presented a lot of real world applications.
    It also provides a lot of guidance on how to expand our knowledge or where to look for it.

  8. Nathan Schad

    Clear explanations that summarized the concepts well. The hands-on examples were useful to learn the Spark modules and syntax to process datasets.

  9. Carlos Daniel Olvera Aguirre

    I think it is an excellent course. The course has everything in one, the topics are interesting and advanced.

  10. Abishek Mazumdar

    Spark ETL sessions are great. Learnt a lot about ETL process in a short period of time. However, a more comprehensive lecture can be benificial by including more ML workflows as a optional section.

  11. Viktar Kazlou

    In general the couse useful for learning Spark from scratch. It will nice to have more complex examples/solutions.

  12. N Murari

    Just awesome, straight to the point. I think if spark streaming section had some more videos that would have been helpful. Overall great course to get a good understanding of spark.

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