Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Processing HiveQL statements

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.