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Big Data & Hadoop · Module 6 of 10

Hive and SQL on big data

Query huge datasets with SQL.

📖 Key ideas

  1. Hive translates HiveQL into distributed jobs.
  2. Tables map onto files in HDFS (schema-on-read).
  3. Partitioning by date/region speeds queries.
  4. Formats: ORC and Parquet are columnar and efficient.
  5. Modern engines: Spark SQL, Presto/Trino, Impala.
💡 Real-life example: Hive is a translator turning simple SQL questions into big cluster jobs.
HiveQLHive's SQL dialect
Schema-on-readSchema applied when reading
PartitionData split by a column into folders
ORC/ParquetColumnar file formats