加快 hive 查询的 5 种方法

1. 使用 Tez

set hive.execution.engine=tez;

2. 使用 ORCFILE。当有多个表 join 时，使用 ORCFile 进行存储，会显著地提高速度。

CREATE TABLE A_ORC (
customerID int, name string, age int, address string
) STORED AS ORC tblproperties ("orc.compress" = "SNAPPY");

3. 使用 VECTORIZATION。会提高 scans, aggregations, filters and joins 等操作的性能。它会把 1024条记录做为一批进行处理，而不是每条记录进行处理。

set hive.vectorized.execution.enabled = true;
set hive.vectorized.execution.reduce.enabled = true;

4. 使用 Cost-based optimization (CBO) 。根据查询代价进行优化。

set hive.cbo.enable=true;
set hive.compute.query.using.stats=true;
set hive.stats.fetch.column.stats=true;
set hive.stats.fetch.partition.stats=true;

需要运行 "analyze" 命令为 CBO 收集表的各种统计信息。

analyze table tbl_student compute statistics;
analyze table tbl_student compute statistics for columns birthday, race;

5. 优化 sql

SELECT clicks.* FROM clicks inner join
(select sessionID, max(timestamp) as max_ts from clicks
group by sessionID) latest
ON clicks.sessionID = latest.sessionID and
clicks.timestamp = latest.max_ts;

使用下面的 sql 代替上面的

SELECT * FROM
(SELECT *, RANK() over (partition by sessionID,
order by timestamp desc) as rank
FROM clicks) ranked_clicks
WHERE ranked_clicks.rank=;