As a rising star, Spark has become the most popular distributed memory computing engine in the open source community, and its functions also cover many areas of big data.
So whether you are a big data engineer or an algorithm engineer such as machine learning, Spark is a computing engine that you must master.
However, in the process of mastering Spark, many obstacles will inevitably be encountered:
For beginners , the charge sub understand the background principle, and distributed operating environment is very difficult in;
Analyze huge amounts of data, master data model good design capability , a personal learning process is difficult to improve the;
The physical resources that can be scheduled at different times are different, and task tuning of massive data becomes difficult .
Do not worry, we've put together a day by the Liao Xuefeng took a number of technical experts and other well-polished 3 months worth 1788 yuan of "Spark full range of knowledge," learning video , engaged in Java, PHP, operation and maintenance work or want to improve This information is especially suitable for people who change careers or want to work in big data related jobs .
Now give it to everyone for free for a limited time! Scan the QR code below to receive it, the hand is slow~
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What can I get from this information?
After watching this video, you will gain:
1. In-depth understanding of the development of Spark programs in the functional programming language Scala;
2. In-depth analysis of the characteristics of Spark's underlying core RDD;
3. In-depth understanding of the RDD caching mechanism and the principle and use of broadcast variables;
4. Master the Spark task submission, task division, and task scheduling process.
More importantly, by learning the knowledge content of this video, you will provide strong support for your future work and interview.
What does this information contain?
1. Spark's memory computing framework-course content introduction
Knowledge points: spark preparation content
2. Develop an introductory case of Spark through IDEA tools
Knowledge point: maven builds scala project
3. Spark's memory computing framework-an introductory case for developing Spark through IDEA tools-code development
Knowledge points: scala syntax, spark program development
4. Spark's in-memory computing framework-the program is marked as a jar package and submitted to the Spark cluster to run
Knowledge points: the use of the program into a jar package and spark-submit to submit tasks
5. Spark's memory computing framework-what is the RDD of Spark's underlying programming abstraction
Knowledge points: Spark's underlying core RDD
6. Spark's memory computing framework-five features of RDD of Spark's underlying programming abstraction
Knowledge points: the characteristics of Spark's underlying core RDD
7. In-depth analysis of the five characteristics of RDD based on word statistical cases
Knowledge points: in-depth analysis of the five features of Spark's underlying core RDD
8. Operator operation classification of Spark's underlying core RDD
Knowledge points: operator classification of the underlying core RDD of spark
9. Dependencies of Spark's underlying core RDD
Knowledge point: the dependency of the underlying core RDD of spark (wide and narrow dependencies)
10. The cache mechanism of Spark's underlying core RDD
Knowledge points: the caching mechanism, application scenarios, how to use, and how to clear the cache of the underlying core RDD of spark
11. Construction and stage division of DAG directed acyclic graph
Knowledge points: DAG directed acyclic graph and stage division
12. Analyze the submission, division and scheduling process of Spark tasks based on the wordcount program
Knowledge points: analysis of spark task submission, division and scheduling process
13. Realize clickstream log analysis case through Spark development
Knowledge point: common RDD operators count/map/distinct/filter/sortByKey use
14. Realize IP attribution query case through Spark development-introduction to requirements
Knowledge point: ip attribution query requirements introduction
15. Realize IP attribution query case through Spark development-code development
Knowledge points: broadcast variables and ip addresses in spark are converted to Long type numbers, and binary query
The information provided by the commencement of it sponsored the original value of 1788 yuan , only to receive a free 128 before (after over-pay to watch)! Friends who need it, please scan the QR code below and add the assistant WeChat to consult and receive.
Free for the first 128 only
In addition, the course bar also cooperated with IT technology big cow teacher Liao Xuefeng and Ali P8 level architect to carefully develop a systematic paid course "Big Data Senior Development Engineer" . The course is in-depth against Ali P6 , and the projects all use real enterprise-level project actual cases. From the use of the framework to the analysis of the source code, we will systematically explain the essential skills of big data technology ecology. The course will also provide services such as job recommendation for large companies to help everyone smoothly embark on the road of advanced big data development. The latest period of the course is enrolling students, and interested friends can also add assistant WeChat consultation!