Hive Tez 减速器 运行 超慢

Hive Tez reducers are running super slow

我加入了多个表,总行数约为 250 亿行。最重要的是,我正在做聚合。下面是我的配置单元设置,我用它来生成最终输出。我不太确定如何调整查询并使其 运行 更快。目前,我正在反复试验,看看是否能产生一些结果,但似乎 working.Mappers 并没有 运行ning 更快,但 reducers 需要永远完成。谁能分享您对此的看法?谢谢。

    SET hive.execution.engine=tez;
    SET hive.exec.dynamic.partition.mode=nonstrict;
    SET hive.qubole.cleanup.partial.data.on.failure=true;
    SET hive.tez.container.size=8192;
    SET tez.task.resource.memory.mb=8192;
    SET tez.task.resource.cpu.vcores=2;
    SET hive.mapred.mode=nonstrict;
    SET hive.qubole.dynpart.use.prefix=true;
    SET hive.vectorized.execution.enabled=true;
    SET hive.vectorized.execution.reduce.enabled =true;
    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;
    SET mapred.reduce.tasks = -1;
    SET hive.auto.convert.join.noconditionaltask.size=2730;
    SET hive.auto.convert.join=true;
    SET hive.auto.convert.join.noconditionaltask=true;
    SET hive.auto.convert.join.noconditionaltask.size=8053063680;
    SET hive.compute.query.using.stats=true;
    SET hive.stats.fetch.column.stats=true;
    SET hive.stats.fetch.partition.stats=true;
    SET mapreduce.job.reduce.slowstart.completedmaps=0.8;
    set hive.tez.auto.reducer.parallelism = true;
    set hive.exec.reducers.max=100;
    set hive.exec.reducers.bytes.per.reducer=1024000000;

SQL:

SELECT D.d
      ,D.b
      ,COUNT(DISTINCT A.x)  AS cnt
      ,SUM(c)               AS sum
 FROM A
LEFT JOIN
       B
ON A.a = B.b
LEFT JOIN
       C 
ON B.b = C.c
JOIN
       D
 ON A.a >= D.d
AND A.a <= D.d
GROUP BY 1,2
CLUSTER BY D.d;

还没有查询计划,所以可能还有其他原因,但这些设置肯定会限制 reducer 的并行度:

set hive.exec.reducers.max=100;
set hive.exec.reducers.bytes.per.reducer=1024000000;

我建议增加允许的 reducer 数量并减少每个 reducer 的字节数,这将增加 reducer 的并行度:

set hive.exec.reducers.max=5000; 
set hive.exec.reducers.bytes.per.reducer=67108864;

Hive 1.2.0+ 还提供自动重写 optimization for count(distinct)。检查此设置,默认情况下应为 true

hive.optimize.distinct.rewrite=true;

如果查询卡在最后一个 reducer 上,则有