Hive is an application that runs on Hadoop, which is a batch-oriented framework for running MapReduce jobs. When you issue a HiveQL statement, Hive determines whether it can return the results immediately or whether it must submit a MapReduce job.
For example, consider the ddb_features table (from Tutorial: Working with Amazon DynamoDB and Apache Hive). The following Hive query prints state abbreviations and the number of summits in each:
SELECT state_alpha, count(*) FROM ddb_features WHERE feature_class = 'Summit' GROUP BY state_alpha;
Hive does not return the results immediately. Instead, it submits a MapReduce job, which is processed by the Hadoop framework. Hive will wait until the job is complete before it shows the results from the query:
AK 2 AL 2 AR 2 AZ 3 CA 7 CO 2 CT 2 ID 1 KS 1 ME 2 MI 1 MT 3 NC 1 NE 1 NM 1 NY 2 OR 5 PA 1 TN 1 TX 1 UT 4 VA 1 VT 2 WA 2 WY 3 Time taken: 8.753 seconds, Fetched: 25 row(s)
Monitoring and canceling
jobs
When Hive launches a Hadoop job, it prints output from that job. The job completion status is updated as the job progresses. In some cases, the status might not be updated for a long time. (This can happen when you are querying a large DynamoDB table that has a low provisioned read capacity setting.)
If you need to cancel the job before it is complete, you can type
Ctrl+C at any time.
