Spark works with a variety of structured data sources including, but not limited to, the following:
- Parquet Files: Apache Parquet is a columnar storage format. More details about the structure of Parquet and how spark makes use of it is available in the Spark SQL chapter.
- Hive tables.
- JDBC: Spark allows the use of JDBC to connect to a wide variety of databases. Of course the data access via JDBC is relatively slow compared to native database utilities.
We'll cover most of the structured sources in Chapter 4, Spark SQL later in this book.
A NoSQL
(originally referring to non SQL, non relational or not only SQL) database provides a mechanism for storage (https://en.wikipedia.org/wiki/Computer_data_storage) and retrieval (https://en.wikipedia.org/wiki/Data_retrieval) of data which is modeled in means other than the tabular relations used in Relational databases (https://en.wikipedia.org/wiki/Relational_database). NoSQL is a relatively...