By Venkat Ankam
- This booklet relies at the newest 2.0 model of Apache Spark and 2.7 model of Hadoop built-in with most typically used tools.
- Learn all Spark stack elements together with newest subject matters akin to DataFrames, DataSets, GraphFrames, established Streaming, DataFrame dependent ML Pipelines and SparkR.
- Integrations with frameworks similar to HDFS, YARN and instruments reminiscent of Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall.
Big info Analytics e-book goals at offering the basics of Apache Spark and Hadoop. All Spark elements – Spark center, Spark SQL, DataFrames, facts units, traditional Streaming, established Streaming, MLlib, Graphx and Hadoop center elements – HDFS, MapReduce and Yarn are explored in higher intensity with implementation examples on Spark + Hadoop clusters.
It is relocating clear of MapReduce to Spark. So, benefits of Spark over MapReduce are defined at nice intensity to harvest merits of in-memory speeds. DataFrames API, info resources API and new information set API are defined for construction mammoth info analytical functions. Real-time info analytics utilizing Spark Streaming with Apache Kafka and HBase is roofed to aid development streaming purposes. New established streaming idea is defined with an IOT (Internet of items) use case. desktop studying strategies are coated utilizing MLLib, ML Pipelines and SparkR and Graph Analytics are lined with GraphX and GraphFrames parts of Spark.
Readers also will get a chance to start with net established notebooks comparable to Jupyter, Apache Zeppelin and knowledge circulation instrument Apache NiFi to research and visualize data.
What you'll learn
- Find out and enforce the instruments and strategies of massive facts analytics utilizing Spark on Hadoop clusters with wide selection of instruments used with Spark and Hadoop
- Understand all of the Hadoop and Spark surroundings components
- Get to grasp the entire Spark parts: Spark middle, Spark SQL, DataFrames, DataSets, traditional and dependent Streaming, MLLib, ML Pipelines and Graphx
- See batch and real-time info analytics utilizing Spark center, Spark SQL, and traditional and dependent Streaming
- Get to grips with info technological know-how and computing device studying utilizing MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall.
About the Author
Venkat Ankam has over 18 years of IT event and over five years in monstrous information applied sciences, operating with buyers to layout and boost scalable enormous information functions. Having labored with a number of consumers globally, he has great adventure in substantial facts analytics utilizing Hadoop and Spark.
He is a Cloudera qualified Hadoop Developer and Administrator and likewise a Databricks qualified Spark Developer. he's the founder and presenter of some Hadoop and Spark meetup teams globally and likes to proportion wisdom with the community.
Venkat has added 1000s of trainings, shows, and white papers within the massive info sphere. whereas this can be his first test at writing a e-book, many extra books are within the pipeline.
Table of Contents
- Big info Analytics at 10,000 foot view
- Getting all started with Apache Hadoop and Apache Spark
- Deep Dive into Apache Spark
- Big information Analytics with Spark SQL, DataFrames, and Datasets
- Real-Time Analytics with Spark Streaming and based Streaming
- Notebooks and Dataflows with Spark and Hadoop
- Machine studying with Spark and Hadoop
- Building suggestion platforms with Spark and Mahout
- Graph Analytics with GraphX
- Interactive Analytics with SparkR
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Extra resources for Big Data Analytics
Big Data Analytics by Venkat Ankam