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Author Archives: Manish Mishra
Introduction to Structured Streaming
Hello!! Knoldus had organized half an hour session on Structured Streaming briefing about the API changes, how it is different from the early Stream Computation paradigm (DStreams) and example API demonstration. Hope you will enjoy. Below are the slides and Video … Continue reading
Posted in apache spark, Scala, Spark, Streaming
1 Comment
Sharing RDD’s states across Spark applications with Apache Ignite
Apache Ignite offers an abstraction over native Spark RDDs such that the state of RDDs can be shared across spark jobs, workers and applications which is not possible with native Spark RDDS. In this blog, we will walk through the … Continue reading
Posted in apache spark, Scala, Spark
Tagged Apache Ignite, apache spark, In-memory computing, Shared RDD, Spark
2 Comments
Controlling RDD Partitions in Apache Spark
In this blog, we will discuss What is RDD partitioning, why Partitioning is important and how to create and use spark Partitioners to minimize the shuffle operations across the nodes in a distributed Spark application. What is Partitioning? Partitioning is a transformation … Continue reading
Build your personalized movie recommender with Scala and Spark
In this blog I will explain what is a recommendation engine in general, and How to build a personalized recommendation model using Scala and Spark Collaborative filtering algorithm. What is a Recommendation Engine? I assume you’ve shopped online for books … Continue reading
Posted in Scala
Tagged apache spark, Collaborative Filtering, machine learning, Recommendation, scala, Spark MLLib
1 Comment
Introduction to Java 8
The Functional Features of Java8 Java 8 was a major release in terms of language and APIs. The language includes several ideas from functional programming like behavior parameterization, passing lambda expression as methods, processing data with stream pipelines etc. The following presentation … Continue reading
Posted in Java, Scala
Tagged Functional Programming, Java 8, Lambda Expressions in Java, Streams
2 Comments
Broadcast variables in Spark, how and when to use them?
As documentation for Spark Broadcast variables states, they are immutable shared variable which are cached on each worker nodes on a Spark cluster. In this blog, we will demonstrate a simple use case of broadcast variables. When to use Broadcast variable? … Continue reading
Aggregating Neighboring vertices with Apache Spark GraphX Library
To get the problems addressed by “Neighborhood Aggregation”, we can think of the queries like: “Who has the maximum number of followers under 20 on twitter?” In this blog, we will learn how to aggregate properties of neighboring vertices on a graph … Continue reading
Posted in apache spark, Scala, Spark
Tagged Big Data, Graph Aggregations, scala, Vertex neighborhood Aggregation
1 Comment
A sample ML Pipeline for Clustering in Spark
Often a machine learning task contains several steps such as extracting features out of raw data, creating learning models to train on features and running predictions on trained models, etc. With the help of the pipeline API provided by Spark, it … Continue reading
Posted in apache spark, big data, Scala, Spark
Tagged K-Means Clustering, machine learning, Machine Learning Pipeline, ML Pipelines, Spark MLLib
11 Comments
Introduction to Machine Learning with Spark (Clustering)
In this blog, we will learn how to group similar data objects using K-means clustering offered by Spark Machine Learning Library. Prerequisites The code example needs only Spark Shell to execute. What is Clustering Clustering is like grouping data objects … Continue reading
Posted in Scala
Tagged apache spark, Big Data, Big Data Analytics, cluster computing, K-Means, machine learning, scala, Spark
