By Venkat Ankam
- This e-book is predicated at the most modern 2.0 model of Apache Spark and 2.7 model of Hadoop built-in with most typically used tools.
- Learn all Spark stack parts together with most up-to-date subject matters corresponding to DataFrames, DataSets, GraphFrames, dependent Streaming, DataFrame established ML Pipelines and SparkR.
- Integrations with frameworks equivalent to HDFS, YARN and instruments resembling Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall.
Big information Analytics booklet goals at supplying the basics of Apache Spark and Hadoop. All Spark parts – Spark middle, Spark SQL, DataFrames, information units, traditional Streaming, dependent Streaming, MLlib, Graphx and Hadoop middle elements – HDFS, MapReduce and Yarn are explored in better intensity with implementation examples on Spark + Hadoop clusters.
It is relocating clear of MapReduce to Spark. So, merits of Spark over MapReduce are defined at nice intensity to harvest merits of in-memory speeds. DataFrames API, facts assets API and new information set API are defined for development immense info analytical functions. Real-time facts analytics utilizing Spark Streaming with Apache Kafka and HBase is roofed to aid construction streaming purposes. New based streaming notion is defined with an IOT (Internet of items) use case. desktop studying strategies are lined utilizing MLLib, ML Pipelines and SparkR and Graph Analytics are coated with GraphX and GraphFrames elements of Spark.
Readers also will get a chance to start with internet dependent notebooks similar to Jupyter, Apache Zeppelin and knowledge circulate instrument Apache NiFi to investigate and visualize data.
What you are going to learn
- Find out and enforce the instruments and methods of massive facts analytics utilizing Spark on Hadoop clusters with large choice of instruments used with Spark and Hadoop
- Understand all of the Hadoop and Spark environment components
- Get to understand all of the Spark elements: Spark middle, Spark SQL, DataFrames, DataSets, traditional and based Streaming, MLLib, ML Pipelines and Graphx
- See batch and real-time facts analytics utilizing Spark center, Spark SQL, and standard and based Streaming
- Get to grips with facts 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 huge facts applied sciences, operating with consumers to layout and advance scalable titanic information purposes. Having labored with a number of consumers globally, he has great event in monstrous information analytics utilizing Hadoop and Spark.
He is a Cloudera qualified Hadoop Developer and Administrator and in addition a Databricks qualified Spark Developer. he's the founder and presenter of some Hadoop and Spark meetup teams globally and likes to percentage wisdom with the community.
Venkat has introduced thousands of trainings, displays, and white papers within the gigantic information sphere. whereas this can be his first try at writing a e-book, many extra books are within the pipeline.
Table of Contents
- Big facts Analytics at 10,000 foot view
- Getting all started with Apache Hadoop and Apache Spark
- Deep Dive into Apache Spark
- Big facts 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 structures with Spark and Mahout
- Graph Analytics with GraphX
- Interactive Analytics with SparkR
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