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Paper’s Introduction At the time of the paper writing, data processing frameworks like MapReduce and its “cousins “ like Hadoop , Pig , Hive , or Spark allow the data consumer to process batch data at scale. On the stream processing side, tools like MillWheel , Spark Streaming , or Storm came to support the user.
As per Apache, “ Apache Spark is a unified analytics engine for large-scale data processing ” Spark is a cluster computing framework, somewhat similar to MapReduce but has a lot more capabilities, features, speed and provides APIs for developers in many languages like Scala, Python, Java and R.
This architecture shows that simulated sensor data is ingested from MQTT to Kafka. Finally, the data is published and visualized on a Java-based custom Dashboard. Learn how to process Wikipedia archives using Hadoop and identify the lived pages in a day. Understand the importance of Qubole in powering up Hadoop and Notebooks.
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