1.TPC-DS下载地址如下

http://www.tpc.org/tpc_documents_current_versions/current_specifications.asp

1.安装依赖

yum-y install gcc gcc-c++ libstdc++-devel bison byacc flex

2.安装

unzip a3083c5a-55ae-49bc-8d6f-cc2ab508f898-tpc-ds-tool.zip

cd v2.3.0/tools

make

3.生成数据

生成10T数据

./dsdgen -scale10000-dir /dfs/data

后台生成数据

100G数据生成(可以不同机器同时生产秩序改并行度和child后面的数字，注意并行度你自己调整，例如我这里是10，那么就要保证有10个child才能保证数据后续是完整的。)

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 1 >nohup.log 2>&1 &

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 2 >nohup.log 2>&1 &

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 3 >nohup.log 2>&1 &

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 5 >nohup.log 2>&1 &

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 6 >nohup.log 2>&1 &

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 7 >nohup.log 2>&1 &

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 8 >nohup.log 2>&1 &

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 9 >nohup.log 2>&1 &

nohup ./dsdgen -scale 100 -dir/dfs/data/  -parallel 10 -child 10 >nohup.log 2>&1 &

1)   将本地数据上传到HDFS

2)   用hadoop-shell命令开始上传数据：

3)   nohup hadoop fs -put /dfs/data/* /tpc_ds > nohup.log 2>&1 &

创建hive中的表

git clone https:

//github

.com

/hortonworks/hive-testbench

.git

[root@namenode01 text]# pwd

/root/hive-testbench/ddl-tpcds/text 有创建表语句，自己安装自己更改下

alltables.sqlanalyze_everything.sql

create database tpc_ds;

create database tpc_ds2;

use tpc_ds;

drop table if exists call_center;

create external table call_center(

cc_call_center_sk        bigint

,    cc_call_center_id         string

,    cc_rec_start_date       string

,    cc_rec_end_date         string

,    cc_closed_date_sk        bigint

,    cc_open_date_sk          bigint

,    cc_name                  string

,    cc_class                 string

,    cc_employees              int

,    cc_sq_ft                  int

,    cc_hours                 string

,    cc_manager               string

,    cc_mkt_id                 int

,    cc_mkt_class             string

,    cc_mkt_desc              string

,    cc_market_manager        string

,    cc_division               int

,    cc_division_name         string

,    cc_company                int

,    cc_company_name          string

,    cc_street_number         string

,    cc_street_name           string

,    cc_street_type            string

,    cc_suite_number          string

,    cc_city                  string

,    cc_county                string

,    cc_state                 string

,    cc_zip                   string

,    cc_country               string

,    cc_gmt_offset            double

,    cc_tax_percentage         double

)

row format delimited fields terminatedby '|'

STORED AS textfile; 还有很多，不一一展现了。

加载数据：

LOAD DATA  inpath '/tpc_ds/call_center*.dat' INTO TABLEcall_center;

创建Partquet列式数据存储

use tpc_ds2;

create external table call_center(

cc_call_center_sk        bigint

,    cc_call_center_id        string

,    cc_rec_start_date       string

,    cc_rec_end_date         string

,    cc_closed_date_sk        bigint

,    cc_open_date_sk          bigint

,    cc_name                  string

,    cc_class                  string

,    cc_employees              int

,    cc_sq_ft                  int

,    cc_hours                 string

,    cc_manager               string

,    cc_mkt_id                 int

,    cc_mkt_class             string

,    cc_mkt_desc              string

,    cc_market_manager        string

,    cc_division               int

,    cc_division_name         string

,    cc_company                int

,    cc_company_name          string

,    cc_street_number          string

,    cc_street_name           string

,    cc_street_type           string

,    cc_suite_number          string

,    cc_city                  string

,    cc_county                string

,    cc_state                 string

,    cc_zip                   string

,    cc_country               string

,    cc_gmt_offset            double

,    cc_tax_percentage         double

)

row format delimited fields terminatedby '|' STORED AS PARQUET;

加载数据到partquet数据到表里：

INSERT OVERWRITE TABLE call_center  SELECT * FROM tpc_ds.call_center; 其他表也类似加载，之后就可以进行性能测试。

SQL语句:

select * from

(selecti_manufact_id,sum(ss_sales_price) sum_sales,avg(sum(ss_sales_price)) over(partition by i_manufact_id) avg_quarterly_sales from item,

store_sales, date_dim, store

where ss_item_sk = i_item_sk and

ss_sold_date_sk = d_date_sk and

ss_store_sk = s_store_sk and

d_month_seq in(1212,1212+1,1212+2,1212+3,1212+4,1212+5,1212+6,1212+7,1212+8,1212+9,1212+10,1212+11)and

((i_category in('Books','Children','Electronics') and

i_class in('personal','portable','reference','self-help') and

i_brand in ('scholaramalgamalg#14','scholaramalgamalg #7','exportiunivamalg #9','scholaramalgamalg #9')) or

(i_category in ('Women','Music','Men')and i_class in ('accessories','classical','fragrances','pants') and

i_brand in ('amalgimporto #1','edupackscholar #1','exportiimporto #1','importoamalg #1')))

group by i_manufact_id, d_qoy ) tmp1where case when avg_quarterly_sales > 0 then abs (sum_sales -avg_quarterly_sales)/ avg_quarterly_sales

else null end > 0.1

order by avg_quarterly_sales,sum_sales,

i_manufact_id

limit 100;

2.   Linux 缓冲

echo 3 >/proc/sys/vm/drop_caches

3.   执行时间