目錄
- 前言
- 將Oracle數(shù)據(jù)庫的MBPS&IOPS By Function查詢導(dǎo)入Vertica數(shù)據(jù)庫
- 用Tableau可視化Vertica數(shù)據(jù)庫的表
- 參考內(nèi)容
前言
本月下旬，我在墨天輪上連續(xù)發(fā)表了幾篇關(guān)于Vertica數(shù)據(jù)庫的原創(chuàng)博客文章，它們按發(fā)表的時(shí)間先后順序分別是：
- 什么是Vertica數(shù)據(jù)庫（英文版）
- 用Tableau可視化Vertica數(shù)據(jù)庫之“DB Time”篇
- 用Tableau可視化Vertica數(shù)據(jù)庫之“LPS&TPS”篇
因?yàn)?b>Vertica數(shù)據(jù)庫非常適合海量數(shù)據(jù)的分析和處理，所以今天這篇文章將要介紹的是將Oracle數(shù)據(jù)庫的MBPS&IOPS By Function性能查詢數(shù)據(jù)導(dǎo)入Vertica數(shù)據(jù)庫，然后用Tableau工具連接到Vertica，并對(duì)導(dǎo)入的性能表進(jìn)行可視化操作。另外，我們知道Oracle數(shù)據(jù)庫的動(dòng)態(tài)性能視圖V$IOSTAT_FUNCTION里有下面的一些數(shù)據(jù)列和對(duì)應(yīng)的數(shù)據(jù)類型：
DESC v$iostat_function
Name Null? Type
----------------------------------------------------------------- -------- --------------------------------------------
FUNCTION_ID NUMBER
FUNCTION_NAME VARCHAR2(18)
SMALL_READ_MEGABYTES NUMBER
SMALL_WRITE_MEGABYTES NUMBER
LARGE_READ_MEGABYTES NUMBER
LARGE_WRITE_MEGABYTES NUMBER
SMALL_READ_REQS NUMBER
SMALL_WRITE_REQS NUMBER
LARGE_READ_REQS NUMBER
LARGE_WRITE_REQS NUMBER
NUMBER_OF_WAITS NUMBER
WAIT_TIME NUMBER其中，我們使用SQL語句查詢V$IOSTAT_FUNCTION中的FUNCTION_ID和FUNCTION_NAME后發(fā)現(xiàn)Oracle的IO按FUNCTION分類總共有14個(gè)不同的類別，請(qǐng)看下面的查詢語句和結(jié)果：
SET PAGESIZE 30
COLUMN function_name FOR a18
SELECT function_id, function_name FROM v$iostat_function ORDER BY 1;
FUNCTION_ID FUNCTION_NAME
----------- ------------------------------------
0 RMAN
1 DBWR
2 LGWR
3 ARCH
4 XDB
5 Streams AQ
6 Data Pump
7 Recovery
8 Buffer Cache Reads
9 Direct Reads
10 Direct Writes
11 Smart Scan
12 Archive Manager
13 Others
14 rows selected.因此，我們需要從兩個(gè)維度（最近1分鐘和最近1小時(shí)）可視化我們所提到的14個(gè)類別（在圖表中也可將其稱作“圖例”）的IO（IO分為MBPS和IOPS兩類，即每秒的IO讀寫容量和每秒的IO讀寫請(qǐng)求）情況。其中，最近1分鐘的數(shù)據(jù)保存在動(dòng)態(tài)性能視圖V$IOFUNCMETRIC里，最近1小時(shí)的數(shù)據(jù)保存在動(dòng)態(tài)性能視圖V$IOFUNCMETRIC_HISTORY上。所以兩個(gè)維度和兩個(gè)IO類別的互相組合，我們將要使用四個(gè)SQL查詢來實(shí)現(xiàn)我們的業(yè)務(wù)需求。
將Oracle數(shù)據(jù)庫的MBPS&IOPS By Function查詢導(dǎo)入Vertica數(shù)據(jù)庫
- 將Oracle數(shù)據(jù)庫的MBPS&IOPS By Function查詢保存為CSV文件
- 將所有CSV文件上傳到Vertica服務(wù)器的/home/dbadmin目錄下
- 用vsql客戶端命令連接到Vertica數(shù)據(jù)庫
- 在Vertica數(shù)據(jù)庫中創(chuàng)建相關(guān)的MBPS&IOPS By Function表
- 使用COPY命令將CSV文件導(dǎo)入剛創(chuàng)建的表中
將Oracle數(shù)據(jù)庫的MBPS&IOPS By Function查詢保存為CSV文件
和前兩篇文章的方法相同，我們?cè)?b>SQL Develooper中分別以腳本方式運(yùn)行下面的四個(gè)SQL查詢并將其保存為CSV文件。具體的操作步驟有些繁瑣，所以這里只貼出SQL代碼，依次（首先，最近1分鐘和最近1小時(shí)的MBPS；其次，最近1分鐘和最近1小時(shí)的IOPS）如下所示：
-- Converting rows to columns Based on I/O Megabytes per Second in Last 1 Minute.
-- Vertical Axis Name: MB Per Sec
SET FEEDBACK off;
SET SQLFORMAT csv;
SET LINESIZE 200
SET PAGESIZE 10
COLUMN sample_time FORMAT a11
COLUMN function_name FORMAT a18
COLUMN io_mbps FORMAT 999,999,999.999
ALTER SESSION SET nls_date_format = 'yyyy-mm-dd hh24:mi:ss';
WITH ifm AS
(
SELECT TO_CHAR(end_time, 'yyyy-mm-dd hh24:mi:ss') sample_time
, function_name
, ROUND((small_read_mbps+small_write_mbps+large_read_mbps+large_write_mbps), 3) io_mbps
FROM v$iofuncmetric
)
SELECT * FROM ifm
PIVOT ( MAX(io_mbps)
FOR function_name IN
( 'Buffer Cache Reads' AS "Buffer Cache Reads"
, 'Direct Reads' AS "Direct Reads"
, 'Direct Writes' AS "Direct Writes"
, 'DBWR' AS "DBWR"
, 'LGWR' AS "LGWR"
, 'ARCH' AS "ARCH"
, 'RMAN' AS "RMAN"
, 'Recovery' AS "Recovery"
, 'Data Pump' AS "Data Pump"
, 'Streams AQ' AS "Streams AQ"
, 'XDB' AS "XDB"
, 'Others' AS "Others"
, 'Archive Manager' AS "Archive Manager"
, 'Smart Scan' AS "Smart Scan"
)
)
ORDER BY sample_time
;-- Converting rows to columns Based on I/O Megabytes per Second in Last 1 Hour (interval by each minute).
-- Vertical Axis Name: MB Per Sec
SET FEEDBACK off;
SET SQLFORMAT csv;
SET LINESIZE 200
SET PAGESIZE 80
COLUMN sample_time FORMAT a11
COLUMN function_name FORMAT a18
COLUMN io_mbps FORMAT 999,999,999.999
ALTER SESSION SET nls_date_format = 'yyyy-mm-dd hh24:mi:ss';
WITH ifmh AS
(
SELECT TO_CHAR(end_time, 'yyyy-mm-dd hh24:mi:ss') sample_time
, function_name
, ROUND((small_read_mbps+small_write_mbps+large_read_mbps+large_write_mbps), 3) io_mbps
FROM v$iofuncmetric_history
)
SELECT * FROM ifmh
PIVOT ( MAX(io_mbps)
FOR function_name IN
( 'Buffer Cache Reads' AS "Buffer Cache Reads"
, 'Direct Reads' AS "Direct Reads"
, 'Direct Writes' AS "Direct Writes"
, 'DBWR' AS "DBWR"
, 'LGWR' AS "LGWR"
, 'ARCH' AS "ARCH"
, 'RMAN' AS "RMAN"
, 'Recovery' AS "Recovery"
, 'Data Pump' AS "Data Pump"
, 'Streams AQ' AS "Streams AQ"
, 'XDB' AS "XDB"
, 'Others' AS "Others"
, 'Archive Manager' AS "Archive Manager"
, 'Smart Scan' AS "Smart Scan"
)
)
ORDER BY sample_time
;-- Converting rows to columns Based on I/O Requests per Second in Last 1 Minute.
-- Horizontal Axis Name: I/O Per Sec
SET FEEDBACK off;
SET SQLFORMAT csv;
SET LINESIZE 200
SET PAGESIZE 10
COLUMN sample_time FORMAT a11
COLUMN function_name FORMAT a18
COLUMN iops FORMAT 999,999,999.999
ALTER SESSION SET nls_date_format = 'yyyy-mm-dd hh24:mi:ss';
WITH ifm AS
(
SELECT TO_CHAR(end_time, 'yyyy-mm-dd hh24:mi:ss') sample_time
, function_name
, ROUND((small_read_iops+small_write_iops+large_read_iops+large_write_iops), 3) iops
FROM v$iofuncmetric
)
SELECT * FROM ifm
PIVOT ( MAX(iops)
FOR function_name IN
( 'Buffer Cache Reads' AS "Buffer Cache Reads"
, 'Direct Reads' AS "Direct Reads"
, 'Direct Writes' AS "Direct Writes"
, 'DBWR' AS "DBWR"
, 'LGWR' AS "LGWR"
, 'ARCH' AS "ARCH"
, 'RMAN' AS "RMAN"
, 'Recovery' AS "Recovery"
, 'Data Pump' AS "Data Pump"
, 'Streams AQ' AS "Streams AQ"
, 'XDB' AS "XDB"
, 'Others' AS "Others"
, 'Archive Manager' AS "Archive Manager"
, 'Smart Scan' AS "Smart Scan"
)
)
ORDER BY sample_time
;-- Converting rows to columns Based on I/O Requests per Second in Last 1 Hour (interval by each minute).
-- Horizontal Axis Name: I/O Per Sec
SET FEEDBACK off;
SET SQLFORMAT csv;
SET LINESIZE 200
SET PAGESIZE 80
COLUMN sample_time FORMAT a11
COLUMN function_name FORMAT a18
COLUMN iops FORMAT 999,999,999.999
ALTER SESSION SET nls_date_format = 'yyyy-mm-dd hh24:mi:ss';
WITH ifmh AS
(
SELECT TO_CHAR(end_time, 'yyyy-mm-dd hh24:mi:ss') sample_time
, function_name
, ROUND((small_read_iops+small_write_iops+large_read_iops+large_write_iops), 3) iops
FROM v$iofuncmetric_history
)
SELECT * FROM ifmh
PIVOT ( MAX(iops)
FOR function_name IN
( 'Buffer Cache Reads' AS "Buffer Cache Reads"
, 'Direct Reads' AS "Direct Reads"
, 'Direct Writes' AS "Direct Writes"
, 'DBWR' AS "DBWR"
, 'LGWR' AS "LGWR"
, 'ARCH' AS "ARCH"
, 'RMAN' AS "RMAN"
, 'Recovery' AS "Recovery"
, 'Data Pump' AS "Data Pump"
, 'Streams AQ' AS "Streams AQ"
, 'XDB' AS "XDB"
, 'Others' AS "Others"
, 'Archive Manager' AS "Archive Manager"
, 'Smart Scan' AS "Smart Scan"
)
)
ORDER BY sample_time
;由于CSV文件的內(nèi)容過多，所以我把它們分別上傳到了我的GitHub，您可以查看這4個(gè)文件：crtc_oracle_io_mbps_in_last_1_minute.csv，crtc_oracle_io_mbps_in_last_1_hour.csv，crtc_oracle_iops_in_last_1_minute.csv和crtc_oracle_iops_in_last_1_hour.csv。
將所有CSV文件上傳到Vertica服務(wù)器的/home/dbadmin目錄下
這里，省略具體的上傳步驟和相關(guān)授權(quán)操作，最終的上傳結(jié)果如下所示（用“<<==”標(biāo)明）：
[dbadmin@test ~]$ ls -lrht
total 184K
drwxr-xr-x 5 dbadmin verticadba 134 Dec 15 14:06 vdb_oracle_perf
......
-rw-r--r-- 1 dbadmin verticadba 225 Dec 23 10:54 crtc_oracle_io_mbps_in_last_1_minute.csv <<==
-rw-r--r-- 1 dbadmin verticadba 3.0K Dec 23 10:56 crtc_oracle_io_mbps_in_last_1_hour.csv <<==
-rw-r--r-- 1 dbadmin verticadba 233 Dec 23 10:57 crtc_oracle_iops_in_last_1_minute.csv <<==
-rw-r--r-- 1 dbadmin verticadba 3.6K Dec 23 10:59 crtc_oracle_iops_in_last_1_hour.csv <<==用vsql客戶端命令連接到Vertica數(shù)據(jù)庫
用Linux命令su切換Vertica數(shù)據(jù)庫服務(wù)器的root用戶到dbadmin用戶，然后用vsql命令進(jìn)行連接，下面是具體的操作過程：
[root@test ~]# su - dbadmin
[dbadmin@test ~]$
[dbadmin@test ~]$ /opt/vertica/bin/vsql -h 127.0.0.1 vdb_oracle_perf dbadmin
Password:
Welcome to vsql, the Vertica Analytic Database interactive terminal.
Type: \h or \? for help with vsql commands
\g or terminate with semicolon to execute query
\q to quit
vdb_oracle_perf=> 在Vertica數(shù)據(jù)庫中創(chuàng)建相關(guān)的MBPS&IOPS By Function表
在public的schema下，分別創(chuàng)建表crtc_oracle_io_mbps_in_last_1_minute，crtc_oracle_io_mbps_in_last_1_hour，crtc_oracle_iops_in_last_1_minute和crtc_oracle_iops_in_last_1_hour。
vdb_oracle_perf=>
vdb_oracle_perf=> CREATE TABLE public.crtc_oracle_io_mbps_in_last_1_minute
vdb_oracle_perf-> (sample_time TIMESTAMP,
vdb_oracle_perf(> buffer_cache_reads NUMBER(12,3),
vdb_oracle_perf(> direct_reads NUMBER(12,3),
vdb_oracle_perf(> direct_writes NUMBER(12,3),
vdb_oracle_perf(> dbwr NUMBER(12,3),
vdb_oracle_perf(> lgwr NUMBER(12,3),
vdb_oracle_perf(> arch NUMBER(12,3),
vdb_oracle_perf(> rman NUMBER(12,3),
vdb_oracle_perf(> recovery NUMBER(12,3),
vdb_oracle_perf(> data_pump NUMBER(12,3),
vdb_oracle_perf(> streams_aq NUMBER(12,3),
vdb_oracle_perf(> xdb NUMBER(12,3),
vdb_oracle_perf(> others NUMBER(12,3),
vdb_oracle_perf(> archive_manager NUMBER(12,3),
vdb_oracle_perf(> smart_scan NUMBER(12,3)
vdb_oracle_perf(> );
CREATE TABLE
vdb_oracle_perf=> vdb_oracle_perf=>
vdb_oracle_perf=> CREATE TABLE public.crtc_oracle_io_mbps_in_last_1_hour
vdb_oracle_perf-> (sample_time TIMESTAMP,
vdb_oracle_perf(> buffer_cache_reads NUMBER(12,3),
vdb_oracle_perf(> direct_reads NUMBER(12,3),
vdb_oracle_perf(> direct_writes NUMBER(12,3),
vdb_oracle_perf(> dbwr NUMBER(12,3),
vdb_oracle_perf(> lgwr NUMBER(12,3),
vdb_oracle_perf(> arch NUMBER(12,3),
vdb_oracle_perf(> rman NUMBER(12,3),
vdb_oracle_perf(> recovery NUMBER(12,3),
vdb_oracle_perf(> data_pump NUMBER(12,3),
vdb_oracle_perf(> streams_aq NUMBER(12,3),
vdb_oracle_perf(> xdb NUMBER(12,3),
vdb_oracle_perf(> others NUMBER(12,3),
vdb_oracle_perf(> archive_manager NUMBER(12,3),
vdb_oracle_perf(> smart_scan NUMBER(12,3)
vdb_oracle_perf(> );
CREATE TABLE
vdb_oracle_perf=> vdb_oracle_perf=>
vdb_oracle_perf=> CREATE TABLE public.crtc_oracle_iops_in_last_1_minute
vdb_oracle_perf-> (sample_time TIMESTAMP,
vdb_oracle_perf(> buffer_cache_reads NUMBER(12,3),
vdb_oracle_perf(> direct_reads NUMBER(12,3),
vdb_oracle_perf(> direct_writes NUMBER(12,3),
vdb_oracle_perf(> dbwr NUMBER(12,3),
vdb_oracle_perf(> lgwr NUMBER(12,3),
vdb_oracle_perf(> arch NUMBER(12,3),
vdb_oracle_perf(> rman NUMBER(12,3),
vdb_oracle_perf(> recovery NUMBER(12,3),
vdb_oracle_perf(> data_pump NUMBER(12,3),
vdb_oracle_perf(> streams_aq NUMBER(12,3),
vdb_oracle_perf(> xdb NUMBER(12,3),
vdb_oracle_perf(> others NUMBER(12,3),
vdb_oracle_perf(> archive_manager NUMBER(12,3),
vdb_oracle_perf(> smart_scan NUMBER(12,3)
vdb_oracle_perf(> );
CREATE TABLE
vdb_oracle_perf=> vdb_oracle_perf=>
vdb_oracle_perf=> CREATE TABLE public.crtc_oracle_iops_in_last_1_hour
vdb_oracle_perf-> (sample_time TIMESTAMP,
vdb_oracle_perf(> buffer_cache_reads NUMBER(12,3),
vdb_oracle_perf(> direct_reads NUMBER(12,3),
vdb_oracle_perf(> direct_writes NUMBER(12,3),
vdb_oracle_perf(> dbwr NUMBER(12,3),
vdb_oracle_perf(> lgwr NUMBER(12,3),
vdb_oracle_perf(> arch NUMBER(12,3),
vdb_oracle_perf(> rman NUMBER(12,3),
vdb_oracle_perf(> recovery NUMBER(12,3),
vdb_oracle_perf(> data_pump NUMBER(12,3),
vdb_oracle_perf(> streams_aq NUMBER(12,3),
vdb_oracle_perf(> xdb NUMBER(12,3),
vdb_oracle_perf(> others NUMBER(12,3),
vdb_oracle_perf(> archive_manager NUMBER(12,3),
vdb_oracle_perf(> smart_scan NUMBER(12,3)
vdb_oracle_perf(> );
CREATE TABLE
vdb_oracle_perf=> 使用COPY命令將CSV文件導(dǎo)入剛創(chuàng)建的表中
在上一步操作中，我們已經(jīng)創(chuàng)建成功了4個(gè)表。現(xiàn)在我們用COPY命令將上傳到Vertica數(shù)據(jù)庫服務(wù)器的4個(gè)CSV文件分別導(dǎo)入到那4個(gè)表中。操作步驟依次為：
vdb_oracle_perf=>
vdb_oracle_perf=> COPY public.crtc_oracle_io_mbps_in_last_1_minute FROM '/home/dbadmin/crtc_oracle_io_mbps_in_last_1_minute.csv' EXCEPTIONS '/home/dbadmin/imp_io_mbps_1.log' DELIMITER AS ',';
NOTICE 7850: In a multi-threaded load, rejected record data may be written to additional files
HINT: Exceptions may be written to files [/home/dbadmin/imp_io_mbps_1.log], [/home/dbadmin/imp_io_mbps_1.log.1], etc
Rows Loaded
-------------
1
(1 row)vdb_oracle_perf=>
vdb_oracle_perf=> COPY public.crtc_oracle_io_mbps_in_last_1_hour FROM '/home/dbadmin/crtc_oracle_io_mbps_in_last_1_hour.csv' EXCEPTIONS '/home/dbadmin/imp_io_mbps_2.log' DELIMITER AS ',';
NOTICE 7850: In a multi-threaded load, rejected record data may be written to additional files
HINT: Exceptions may be written to files [/home/dbadmin/imp_io_mbps_2.log], [/home/dbadmin/imp_io_mbps_2.log.1], etc
Rows Loaded
-------------
61
(1 row)vdb_oracle_perf=>
vdb_oracle_perf=> COPY public.crtc_oracle_iops_in_last_1_minute FROM '/home/dbadmin/crtc_oracle_iops_in_last_1_minute.csv' EXCEPTIONS '/home/dbadmin/imp_iops_1.log' DELIMITER AS ',';
NOTICE 7850: In a multi-threaded load, rejected record data may be written to additional files
HINT: Exceptions may be written to files [/home/dbadmin/imp_iops_1.log], [/home/dbadmin/imp_iops_1.log.1], etc
Rows Loaded
-------------
1
(1 row)vdb_oracle_perf=>
vdb_oracle_perf=> COPY public.crtc_oracle_iops_in_last_1_hour FROM '/home/dbadmin/crtc_oracle_iops_in_last_1_hour.csv' EXCEPTIONS '/home/dbadmin/imp_iops_2.log' DELIMITER AS ',';
NOTICE 7850: In a multi-threaded load, rejected record data may be written to additional files
HINT: Exceptions may be written to files [/home/dbadmin/imp_iops_2.log], [/home/dbadmin/imp_iops_2.log.1], etc
Rows Loaded
-------------
61
(1 row)
vdb_oracle_perf=> 用Tableau可視化Vertica數(shù)據(jù)庫的表
- 按Function Name分類的最近1分鐘的IO MBPS
- 按Function Name分類的最近1小時(shí)的IO MBPS
- 按Function Name分類的最近1分鐘的IOPS
- 按Function Name分類的最近1小時(shí)的IOPS
按Function Name分類的最近1分鐘的IO MBPS
打開Tableau Desktop工具，然后連接到Vertica數(shù)據(jù)庫，選擇schema為public，然后將表crtc_oracle_io_mbps_in_last_1_minute拖動(dòng)到指定位置，點(diǎn)擊底部的工作表，進(jìn)入工作表編輯區(qū)。詳見下面兩個(gè)屏幕截圖：
接著，將工作區(qū)中左側(cè)“數(shù)據(jù)”標(biāo)簽卡內(nèi)“表”的度量名稱Sample Time用鼠標(biāo)拖到位于工作區(qū)上方標(biāo)簽名為“列”的右側(cè)“標(biāo)簽框”中，同樣的方法，將“表”的14個(gè)度量值分別拖到位于工作區(qū)上方標(biāo)簽名為“行”的右側(cè)“標(biāo)簽框”中，屏幕截圖如下所示：
然后將標(biāo)簽名為“行”內(nèi)的其余13個(gè)度量依次用鼠標(biāo)拖動(dòng)到工作區(qū)中部的圖表縱坐標(biāo)軸名稱為“Smart Scan”的區(qū)域，也就是將這14個(gè)度量都合并到一個(gè)縱坐標(biāo)軸上，順便修改圖表的名稱和縱坐標(biāo)軸名稱，最終的效果如圖所示：
因?yàn)槊總€(gè)度量在最近1分鐘的數(shù)據(jù)只有一個(gè)值顯示，顯然，所有度量在縱坐標(biāo)軸上顯示的話，這個(gè)柱狀條形圖看起來很臃腫！因此，將這個(gè)14個(gè)度量換到橫坐標(biāo)軸上，詳見下面的兩個(gè)屏幕截圖：
正如我們所看到的，只有Lgwr和Others這兩個(gè)度量有取值。
按Function Name分類的最近1小時(shí)的IO MBPS
因?yàn)樯弦画h(huán)節(jié)我們已經(jīng)非常詳細(xì)地說明了在Tablesau Desktop中可視化表crtc_oracle_io_mbps_in_last_1_minute的每一步驟，所以在這里，我們進(jìn)行快速地操作，見如下屏幕截圖。
最終，按Function Name分類的最近1小時(shí)的IO MBPS的面積堆疊圖是這樣的：
按Function Name分類的最近1分鐘的IOPS
這14個(gè)度量均在縱坐標(biāo)軸上顯示的條形柱狀圖為：
接著，我們將那14個(gè)度量都轉(zhuǎn)換到橫坐標(biāo)軸上顯示。其中，有取值的4個(gè)度量對(duì)應(yīng)的屏幕截圖分別如下所示：
按Function Name分類的最近1小時(shí)的IOPS
最近1小時(shí)的IOPS的面積堆疊圖設(shè)置相對(duì)簡(jiǎn)單，最終效果見下圖：
以上就是這篇文章用Tableau可視化Vertica數(shù)據(jù)庫之“MBPS&IOPS By Function”篇的所有內(nèi)容。另外，您也可以從acquire_io_mbps_by_function.sql和acquire_iops_by_function.sql查看我前面提到的所有SQL源代碼。如果您有好的建議或意見，歡迎在文章底部的評(píng)論區(qū)提出，我將逐條閱讀，并在最快時(shí)間內(nèi)回復(fù)。
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