hive 小文件分析

1、获取fsimage文件:

hdfs dfsadmin -fetchImage /data/xy/

2、从二进制文件解析:

hdfs oiv -i /data/xy/fsimage_0000000019891608958 -t /data/xy/tmpdir -o /data/xy/out -p Delimited -delimiter ","

3、创建hive表

create database if not exists hdfsinfo;

use hdfsinfo;

CREATE TABLE fsimage_info_csv(

path string,

replication int,

modificationtime string,

accesstime string,

preferredblocksize bigint,

blockscount int,

filesize bigint,

nsquota string,

dsquota string,

permission string,

username string,

groupname string)

ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe'

WITH SERDEPROPERTIES ('field.delim'=',', 'serialization.format'=',')

STORED AS INPUTFORMAT 'org.apache.hadoop.mapred.TextInputFormat';

4、存储HDFS元数据加载进hive中

hdfs dfs -put /data/xy/out /user/hive/warehouse/hdfsinfo.db/fsimage_info_csv/

hdfs dfs -ls /user/hive/warehouse/hdfsinfo.db/fsimage_info_csv/

Hive: MSCK REPAIR TABLE hdfsinfo.fsimage_info_csv;

select * from hdfsinfo.fsimage_info_csv limit 5;

5、统计叶子目录下小文件数据量(4194304 H字节,即<4M)

SELECT

dir_path ,

COUNT(*) AS small_file_num,

modificationtime,

accesstime

FROM

( SELECT

modificationtime,

accesstime,

relative_size,

dir_path

FROM

(

SELECT

(CASE filesize < 4194304 WHEN TRUE THEN 'small' ELSE 'large' END) AS relative_size,

modificationtime,

accesstime,

split(

substr(

concat_ws('/', split(PATH, '/')),

1,

length(concat_ws('/', split(PATH, '/'))) - length(last_element) - 1

),

',')0 as dir_path

FROM (

SELECT

modificationtime,

accesstime,

filesize,

PATH,

split(PATH, '/')size(split(PATH, '/')) - 1 as last_element

FROM hdfsinfo.fsimage_info_csv

) t0 ) t1

WHERE

relative_size='small') t2

GROUP BY

dir_path,modificationtime,accesstime

ORDER BY

small_file_num desc

limit 500;

5、统计叶子目录下小文件数据量(4194304 H字节,即<4M)

SELECT

dir_path,

COUNT(*) AS small_file_num

FROM

( SELECT

relative_size,

dir_path

FROM

(

SELECT

(CASE filesize < 41943040 WHEN TRUE THEN 'small' ELSE 'large' END) AS relative_size,

split(

substr(

concat_ws('/', split(PATH, '/')),

1,

length(concat_ws('/', split(PATH, '/'))) - length(last_element) - 1

),

',')0 as dir_path

FROM (

SELECT

filesize,

PATH,

split(PATH, '/')size(split(PATH, '/')) - 1 as last_element

FROM hdfsinfo.fsimage_info_csv

WHERE

permission not LIKE 'd%'

) t0 ) t1

WHERE

relative_size='small') t2

GROUP BY

dir_path

ORDER BY

small_file_num desc

limit 50000;

相关推荐
卷毛迷你猪19 小时前
快速实验篇(A11)数据集成与多维分析:从单实验产出到跨实验宽表
hive·hadoop
西木莉21 小时前
数据仓库概述
数据仓库
卷毛迷你猪2 天前
快速实验篇(A10)短序列上 SPI 的失效机制
hadoop
Francek Chen2 天前
【大数据处理与分析】数据仓库Hive:04 数据仓库Hive概述
大数据·数据仓库·hive·hadoop·分布式
Gl�ria2 天前
Hadoop/YARN 集群缩容:下线DN节点
大数据·hadoop·分布式
计算机源码社2 天前
基于大数据技术的台北市住宅价格影响因素挖掘与可视化分析-基于Python与Hadoop的台北市住宅价格数据仓库构建与可视化
大数据·hadoop·python·数据分析·spark·毕业设计·数据可视化
计算机源码社2 天前
基于Hadoop+Spark的乳腺癌病理数据可视化分析系统 基于K-Means聚类与PCA降维的乳腺癌形态特征分析系统
大数据·hadoop·python·数据分析·spark·毕业设计·数据可视化
Moshow郑锴3 天前
从“水库”到“直饮水站”:重新理解 Data Mart 与 Data Lake、Data Lakehouse、Data Warehouse 的区别
数据仓库·data·湖仓一体
躺柒3 天前
读数据架构知识体系指南01关系数据仓库(上)
数据仓库·架构·数据分析·spark·数据湖·关系数据库·企业数据仓库
卷毛迷你猪3 天前
快速实验篇(A9-2)Python vs MapReduce:小批量任务的工具选择
大数据·hadoop