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Building a real-time big data pipeline 10: Spark Streaming, Kafka, Java

Spark Streaming is an extension of the core Apache Spark platform that enables scalable, high-throughput, fault-tolerant processing of data streams; written in Scala but offers Scala, Java, R and Python APIs to work with. It takes data from the sources like Kafka, Flume, Kinesis, HDFS, S3 or Twitter. This data can be further processed using

Building a real-time big data pipeline 7 : Spark MLlib, Regression, Java

Apache Spark MLlib is a distributed framework that provides many utilities useful for machine learning tasks, such as: Classification, Regression, Clustering, Dimentionality reduction and, Linear algebra, statistics and data handling. >>>

Building a real-time big data pipeline 5 : NoSQL, Java

Apache Cassandra is a distributed NoSQL database (DB) which is used for handling Big data and real-time web applications. NoSQL stands for “Not Only SQL” or “Not SQL”. NoSQL database is a non-relational data management system, that does not require a fixed schema. >>>

Building a real-time big data pipeline 1 : Kafka, RESTful, Java

Building a real-time big data pipeline 1 : Kafka, RESTful, Java Updated on September 20, 2021 Apache Kafka is used for building real-time data pipelines and streaming apps. Kafka is a message broker, which helps transmit messages from one system to another. Zookeeper is required to run a Kafka Cluster. Apache ZooKeeper is primarily used