下面是etl生成的查询
查询-
SELECT infaHiveSysTimestamp('SS') as a0, 7991 as a1, single_use_subq30725.a1 as a2, SUBSTR(SUBSTR(single_use_subq30725.a2, 0, 5), 0, 5) as a3, CAST(1 AS SMALLINT) as a4, single_use_subq30725.a3 as a5, single_use_subq30725.a4 as a6, SUBSTR(SUBSTR(SUBSTR(single_use_subq30725.a8, (CASE WHEN 12 < (- LENGTH(single_use_subq30725.a8)) THEN 0 ELSE 12 END), 104857600), 0, 20), 0, 20) as a7, infaNativeUDFCallString('TO_CHAR', single_use_subq30725.a5) as a8, infaHiveSysTimestamp('SS') as a9, CAST(infaNativeUDFCallDate('TRUNC', single_use_subq30725.a6, 'DD') AS DATE) as a10 FROM (SELECT (CASE WHEN 1 = t1.a1 THEN t1.a0 ELSE CAST(NULL AS TIMESTAMP) END) as a0, infaNativeUDFCallDate('TRUNC', (CASE WHEN 1 = t1.a1 THEN t1.a0 ELSE CAST(NULL AS TIMESTAMP) END), 'DD') as a1
FROM
(
SELECT MAX(t1.a0) as a0, MAX(t1.a1) as a1
FROM (
SELECT mstr_load_audit.last_run_ts as a0, 1 as a1 FROM mstr_etl.mstr_load_audit WHERE interface_name='m_CTM_RAWTLogData_target_tbl'
) t1
)t1
) single_use_subq39991
JOIN (
SELECT w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.CREATE_TS as a0, CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.txACTION_ID AS STRING) as a1, SUBSTR(SUBSTR(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.STORE_NUM AS DECIMAL(18, 0))), (CASE WHEN 0 < (- LENGTH(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.STORE_NUM AS DECIMAL(18, 0))))) THEN 0 ELSE 0 END), 10), (CASE WHEN 0 < (- LENGTH(SUBSTR(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.STORE_NUM AS DECIMAL(18, 0))), (CASE WHEN 0 < (- LENGTH(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.STORE_NUM AS DECIMAL(18, 0))))) THEN 0 ELSE 0 END), 10))) THEN 0 ELSE 0 END), 10) as a2, SUBSTR(SUBSTR(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.LANE_NUM AS DECIMAL(18, 0))), (CASE WHEN 0 < (- LENGTH(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.LANE_NUM AS DECIMAL(18, 0))))) THEN 0 ELSE 0 END), 10), (CASE WHEN 0 < (- LENGTH(SUBSTR(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.LANE_NUM AS DECIMAL(18, 0))), (CASE WHEN 0 < (- LENGTH(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.LANE_NUM AS DECIMAL(18, 0))))) THEN 0 ELSE 0 END), 10))) THEN 0 ELSE 0 END), 10) as a3, SUBSTR(SUBSTR(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.tx_NUM AS DECIMAL(18, 0))), (CASE WHEN 0 < (- LENGTH(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.tx_NUM AS DECIMAL(18, 0))))) THEN 0 ELSE 0 END), 20), (CASE WHEN 0 < (- LENGTH(SUBSTR(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.tx_NUM AS DECIMAL(18, 0))), (CASE WHEN 0 < (- LENGTH(infaNativeUDFCallString('TO_CHAR', CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.tx_NUM AS DECIMAL(18, 0))))) THEN 0 ELSE 0 END), 20))) THEN 0 ELSE 0 END), 20) as a4, CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.LOYALTY_DEV_NUM AS DECIMAL(28, 0)) as a5, CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.tx_DT AS TIMESTAMP) as a6, CAST(w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.ETL_LOAD_DT AS TIMESTAMP) as a7, w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.tx_TS as a8
FROM
sourcedb.W5883634877684653839_Read_lcl_tlog_raw_2_VIEW__m_CTM_RAWTLogData_target_tbl
)
single_use_subq30725
WHERE (single_use_subq39991.a0 < single_use_subq30725.a0) AND (single_use_subq39991.a1 <= single_use_subq30725.a7)]
由于此查询是在配置单元下推模式下生成的,因此我们在sql环境中添加了以下设置
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.exec.orc.split.strategy=BI;
set hive.merge.tezfiles=true;
但我们没有看到任何重大进展。我们确实可以选择在传统的批处理模式下移动这个作业—我们通过shell脚本来运行它。是否可以通过减少执行时间对查询进行任何更改。我相信我们可以摆脱所有类型转换,减少执行时间。有没有别的事,我们可以试试。
1条答案
按热度按时间cs7cruho1#
加入您的查询:
用作交叉联接,因为没有指定on条件。在此交叉连接之后,将使用
WHERE (single_use_subq39991.a0 < single_use_subq30725.a0) AND (single_use_subq39991.a1 <= single_use_subq30725.a7)
实际上,它不乘行,应该作为Map联接使用,因为第一个子查询最多返回一行:添加此设置以启用Map联接:
set hive.auto.convert.join=true;
检查explain输出中是否有map join。但最大的问题不是这个十字(Map?)连接本身。当在第二个查询中读取表时,它防止 predicate 下推在联接之前工作。
我建议删除join并计算一次第一个查询并提供
a0
以及a1
作为where
条款。这样就可以消除不必要的连接, predicate 下推可能直接起作用。例如,ppd可应用于此列:
w5883634877684653839_read_lcl_tlog_raw_2_view__m_ctm_rawtlogdata_target_tbl.CREATE_TS as a0
检查ppd和其他性能设置:https://stackoverflow.com/a/48296562/2700344