Introduction to Impala Application Development

Introduction to Impala

Impala provides fast, interactive SQL queries directly on your Apache Hadoop data stored in HDFS, HBase, or Object Storage Service (OBS). In addition to using the same unified storage platform, Impala also uses the same metadata, SQL syntax (Hive SQL), ODBC driver, and user interface (Impala query UI in Hue) as Apache Hive. This provides a familiar and unified platform for real-time or batch-oriented queries. Impala is an addition to tools available for querying big data. It does not replace the batch processing frameworks built on MapReduce such as Hive. Hive and other frameworks built on MapReduce are best suited for long running batch jobs.

Impala provides the following features:

• Most common SQL-92 features of Hive Query Language (HiveQL) including SELECT, JOIN, and aggregate functions
• HDFS, HBase, and OBS storage, including:
  • HDFS file formats: delimited text files, Parquet, Avro, SequenceFile, and RCFile
  • Compression codecs: Snappy, GZIP, Deflate, BZIP
• Common data access interfaces, including:
  • JDBC driver
  • ODBC driver
  • Hue Beeswax and the Impala query UI
• impala-shell command line interface
• Kerberos authentication

Impala applies to offline analysis (such as log and cluster status analysis) of real-time data queries, large-scale data mining (such as user behavior analysis, interest region analysis, and region display), and other scenarios.