By Venkat Ankam
- This ebook relies at the most up-to-date 2.0 model of Apache Spark and 2.7 model of Hadoop built-in with most ordinarily used tools.
- Learn all Spark stack parts together with most modern subject matters similar to DataFrames, DataSets, GraphFrames, based Streaming, DataFrame established ML Pipelines and SparkR.
- Integrations with frameworks reminiscent of HDFS, YARN and instruments corresponding to Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall.
Big information Analytics e-book goals at supplying the basics of Apache Spark and Hadoop. All Spark elements – Spark center, Spark SQL, DataFrames, facts units, traditional Streaming, based 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, merits of Spark over MapReduce are defined at nice intensity to harvest advantages of in-memory speeds. DataFrames API, facts assets API and new info set API are defined for construction large information analytical functions. Real-time information analytics utilizing Spark Streaming with Apache Kafka and HBase is roofed to assist construction streaming functions. New based streaming thought is defined with an IOT (Internet of items) use case. computing device studying innovations are coated utilizing MLLib, ML Pipelines and SparkR and Graph Analytics are coated with GraphX and GraphFrames parts of Spark.
Readers also will get a chance to start with net dependent notebooks similar to Jupyter, Apache Zeppelin and information circulate device Apache NiFi to research 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 wide selection of instruments used with Spark and Hadoop
- Understand all of the Hadoop and Spark surroundings components
- Get to grasp the entire Spark elements: Spark center, Spark SQL, DataFrames, DataSets, traditional and dependent Streaming, MLLib, ML Pipelines and Graphx
- See batch and real-time information analytics utilizing Spark middle, Spark SQL, and traditional and based Streaming
- Get to grips with information technology and computer studying utilizing MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall.
About the Author
Venkat Ankam has over 18 years of IT adventure and over five years in mammoth info applied sciences, operating with consumers to layout and strengthen scalable colossal information functions. Having labored with a number of consumers globally, he has large adventure in enormous facts 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 brought thousands of trainings, displays, and white papers within the huge facts 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 began 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 advice structures with Spark and Mahout
- Graph Analytics with GraphX
- Interactive Analytics with SparkR
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Big Data Analytics by Venkat Ankam