Describe the approach you would use to build a Hadoop data pipeline for real-time analytics from social media data streams.
- Apache Flink for ingestion, Apache Hadoop MapReduce for processing, and Apache Hive for storage
- Apache Flume for ingestion, Apache Spark Streaming for processing, and Apache Cassandra for storage
- Apache Kafka for ingestion, Apache Spark for processing, and Apache HBase for storage
- Apache Sqoop for ingestion, Apache Storm for processing, and Apache HDFS for storage
The approach for building a Hadoop data pipeline for real-time analytics from social media data streams involves using Apache Sqoop for ingestion, Apache Storm for processing real-time data, and Apache HDFS for storage. This combination ensures efficient data transfer, real-time processing, and scalable storage.
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