Load CSV Data into Couchbase using Apache Spark

Apache Spark is an efficient tool for processing massive amounts of data, performing significantly better than MapReduce. It works well in combination with Couchbase through the Couchbase Spark Connector. To load CSV data into Couchbase using Apache Spark, one needs to include Spark Core, Spark SQL, Spark CSV, and the Couchbase Spark Connector as dependencies. The raw data is loaded into an Apache Spark DataFrame, which can be queried using Spark SQL. The DataFrame is then prepared for saving to Couchbase by mapping the id value to a document id. Finally, the project can be executed using Maven and the `spark-submit` command, which may take some time depending on the size of the dataset and the speed of the computer or server.

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