Greenplum數(shù)據(jù)庫基礎(chǔ)培訓(xùn)

1、Wei.LiSenior Data ArchitectureAlpine Solution2010/05l 海量并行處理 (Massively Parallel Processing) DBMSl 基于 PostgreSQL 8.2 相同的客戶端功能 增加支持并行處理的技術(shù) 增加支持?jǐn)?shù)據(jù)倉庫和BI的特性 外部表(external tables)/并行加載(parallel loading) 資源管理 查詢優(yōu)化器增強(qiáng)(query optimizer enhancements)l psqll pgAdmin IIIl ODBC/Datadirectl JDBCl Perl DBIl Pythonl

2、 libpqlOLE DBl 訪問系統(tǒng)的入口l 數(shù)據(jù)庫偵聽進(jìn)程 (postgres)l 處理所有用戶連接l 建立查詢計劃l 協(xié)調(diào)工作處理過程l 管理工具l 系統(tǒng)目錄表和元數(shù)據(jù)（數(shù)據(jù)字典）l 不存放任何用戶數(shù)據(jù)l 每段（Segment）存放一部分用戶數(shù)據(jù)l 一個系統(tǒng)可以有多段l 用戶不能直接存取訪問l 所有對段的訪問都經(jīng)過Masterl 數(shù)據(jù)庫監(jiān)聽進(jìn)程(postgres)監(jiān)聽來自Master的連接l Greenplum數(shù)據(jù)庫之間的連接層l 進(jìn)程間協(xié)調(diào)和管理l 基于千兆以太網(wǎng)架構(gòu)l 屬于系統(tǒng)內(nèi)部私網(wǎng)配置l 支持兩種協(xié)議：TCP or UDPl Standby 節(jié)點用于當(dāng) Master 節(jié)點損壞時提

3、供 Master 服務(wù)l Standby 實時與 Master 節(jié)點的 Catalog 和事務(wù)日志保持同步l 每個Segment的數(shù)據(jù)冗余存放在另一個Segment上，數(shù)據(jù)實時同步l 當(dāng)Primary Segment失敗時，Mirror Segment將自動提供服務(wù)l Primary Segment恢復(fù)正常后，使用gprecoverseg F 同步數(shù)據(jù)。l Hash分布 CREATE TABLE DISTRIBUTED BY (column ,) 同樣數(shù)值的內(nèi)容被分配到同一個Segment上l 循環(huán)分布 CREATE TABLE DISTRIBUTED RANDOMLY 具有同樣數(shù)值的行內(nèi)容并

4、不一定在同一個Segment上表分布的策略表分布的策略-并行計算的基礎(chǔ)并行計算的基礎(chǔ)查詢命令的執(zhí)行查詢命令的執(zhí)行l(wèi) 舉例說明：按卡號、客戶號、機(jī)構(gòu)的分布方式優(yōu)劣點查詢命令的執(zhí)行查詢命令的執(zhí)行SELECT customer, amount FROM sales JOIN customer USING (cust_id) WHERE date=04302008;l 將一張大表邏輯性地分成多個部分，如按照分區(qū)條件進(jìn)行查詢，將減少數(shù)據(jù)的掃描范圍，提高系統(tǒng)性能。l 提高對于特定類型數(shù)據(jù)的查詢速度和性能l 也可以更方便數(shù)據(jù)庫的維護(hù)和更新l 兩種類型: Range分區(qū) (日期范圍或數(shù)字范圍)/如日期、價格等

5、 List 分區(qū),例如地區(qū)、產(chǎn)品等l Greenplum中的表分區(qū)在使用中具有總表的繼承性，并通過Check參數(shù)指定相應(yīng)的子表l 分區(qū)的子表依然根據(jù)分布策略分布在各segment上l 分區(qū)是一種非常有用的優(yōu)化措施，例如一年的交易按交易日期分區(qū)后，查詢一天的交易性能將提高365倍！Segment 1ASegment 1BSegment 1CSegment 1DSegment 2ASegment 2BSegment 2CSegment 2DSegment 3ASegment 3BSegment 3CSegment 3DJan 2005Feb 2005Mar 2005Apr 2005May 2005

6、Jun 2005Jul 2005Aug 2005Sep 2005Oct 2005Nov 2005Dec 2005每個分區(qū)表的數(shù)據(jù)平均分布到各個節(jié)點表分區(qū)可減少數(shù)據(jù)的搜索范圍，提高查詢性能Segment 1ASegment 1BSegment 1CSegment 1DSegment 2ASegment 2BSegment 2CSegment 2DSegment 3ASegment 3BSegment 3CSegment 3DSegment 1ASegment 1BSegment 1CSegment 1DSegment 2ASegment 2BSegment 2CSegment 2DSegment

7、 3ASegment 3BSegment 3CSegment 3DSegment 1ASegment 1BSegment 1CSegment 1DSegment 2ASegment 2BSegment 2CSegment 2DSegment 3ASegment 3BSegment 3CSegment 3DSELECT COUNT(*) FROM orders WHERE order_date= Oct 20 2005 AND order_date Oct 27 2005VSHash DistributionHash Distribution+ Table PartitioningSegment

8、 1ASegment 1BSegment 1CSegment 1DSegment 2ASegment 2BSegment 2CSegment 2DSegment 3ASegment 3BSegment 3CSegment 3Dl 壓縮存儲 支持ZLIB和QUICKLZ方式的壓縮,壓縮比可到10:1 壓縮表只能是Append Only方式 壓縮數(shù)據(jù)不一定會帶來性能的下降，壓縮表將消耗CPU資源，而減少I/O資源占用l 語法CREATE TABLE foo (a int, b text) WITH (appendonly=true, compresstype=zlib, compresslevel

9、=5); l Greenplum支持行或列存儲模式 列模式目前只支持Append Only 如果常用的查詢只取表中少量字段，則列模式效率更高，如查詢需要取表中的大量字段，行模式效率更高 語法： CREATE TABLE sales2 (LIKE sales) WITH (appendonly=true, orientation=column); 效率比較測試：測試1：需要去表中所有字段，此時行存儲更快。select * from dw_ods.s1_sema_scmcaccp_row where crdacct_nbr= 4033930000166380411;41秒select * from

10、 dw_ods.s1_sema_scmcaccp_col where crdacct_nbr= 4033930000166380411;116秒測試2：只取表中少量字段，列存儲更快select crdacct_status from dw_ods.s1_sema_scmcaccp_row where crdacct_nbr= 4033930000166380411;35秒select crdacct_status from dw_ods.s1_sema_scmcaccp_col where crdacct_nbr= 4033930000166380411;3秒l 外部表的特征 Read-onl

11、y 數(shù)據(jù)存放在數(shù)據(jù)庫外 可執(zhí)行SELECT, JOIN, SORT等命令，類似正規(guī)表的操作l 外部表的優(yōu)點 并行方式加載 ETL的靈活性 格式錯誤行的容錯處理 支持多種數(shù)據(jù)源l 兩種方式 External Tables: 基于文件 Web Tables: 基于URL或指令l 利用并行數(shù)據(jù)流引擎，Greenplum可以直接用SQL操作外部表l 數(shù)據(jù)加載完全并行Master主機(jī)Segment主機(jī)內(nèi)部互聯(lián)網(wǎng)千兆以太網(wǎng)交換機(jī)gpfdistgpfdistSegment主機(jī)Segment主機(jī)Segment主機(jī)外部表文件外部表文件ETL服務(wù)器內(nèi)部網(wǎng)絡(luò)l 并行數(shù)據(jù)加載提供最好的性能l 能夠處理遠(yuǎn)程存儲的文件l

12、 采用HTTP協(xié)議l 200 MB/s data distribution rate per gpfdistl gpfdist文件分發(fā)守護(hù)進(jìn)程啟動:gpfdist -d /var/load_files/expenses -p 8080 -l /home/gpadmin/log &l 外部表定義:CREATE EXTERNAL TABLE ext_expenses ( name text, date date, amount float4, description text )LOCATION (gpfdist/etlhost:8081/*,gpfdist/etlhost:8082/*)

13、FORMAT TEXT (DELIMITER |)ENCODING UTF-8LOG ERRORS INTO ext_expenses_loaderrors SEGMENT REJECT LIMIT 10000 ROWS ;lLoad good rows and catch poorly formatted rows, such as: rows with missing or extra attributes rows with attributes of the wrong data type rows with invalid client encoding sequenceslDoes

14、 not apply to constraint errors: PRIMARY KEY, NOT NULL, CHECK or UNIQUE constraintslOptional error handling clause for external tables:LOG ERRORS INTO error_table SEGMENT REJECT LIMIT count ROWS | PERCENT( PERCENT based on gp_reject_percent_threshold parameter )lExampleCREATE EXTERNAL TABLE ext_cust

15、omer (id int, name text, sponsor text) LOCATION ( gpfdist:/filehost:8081/*.txt ) FORMAT TEXT ( DELIMITER | NULL ) LOG ERRORS INTO err_customer SEGMENT REJECT LIMIT 5 ROWS; l Data resides outside the databasel No database statistics for external table datal Not meant for frequent or ad-hoc accessl Ca

16、n manually set rough statistics in pg_class: UPDATE pg_class SET reltuples=400000, relpages=400 WHERE relname=myexttable;l PostgreSQL commandSupport loading and unloadingOptimized for loading a large number of rowsLoads all rows in one command (not parallel)Loads data from a file or from standard in

17、putSupports error handling as does external tablesl EXAMPLECOPY mytable FROM /data/myfile.csv WITH CSV HEADER; （文件生成在Master）COPY mytable FROM /data/myfile.csv WITH CSV HEADER;（文件生成在本地）COPY country FROM /data/gpdb/country_data WITH DELIMITER | LOG ERRORS INTO err_country SEGMENT REJECT LIMIT 10 ROWS;

18、l Drop indexes and recreate after load Increase maintenance_work_mem parameter to speed up CREATE INDEX operationsl Run ANALYZE after loadl Run VACUUM after load errors、delete、upate。l Do not use ODBC INSERT to load large volumes of datal 限制查詢隊列的激活數(shù)l 防止系統(tǒng)過載(CPU, disk I/O, memory)l Resource Queue Limi

19、ts ACTIVE THRESHOLDEXAMPLE: CREATE RESOURCE QUEUE adhoc ACTIVE THRESHOLD 10 IGNORE THRESHOLD 1000.0; COST THRESHOLDEXAMPLES: CREATE RESOURCE QUEUE batch1 COST THRESHOLD 1000000.0 NOOVERCOMMIT;CREATE RESOURCE QUEUE batch1 COST THRESHOLD 1e+6;l Highly interactive web-based performance monitoringl Real

20、-time and historic views of:Resource utilizationQueries and query internalsDashboardSystem MetricsQuery MonitorBackups and Restoresl Parallel backups (gp_dump)l Parallel restores (gp_restore)l Automating dump/restores (gpcrondump, gpdbrestore)l Non-parallel backups and restores(pg_dump/pg_restore/ps

21、ql)l 用于在同構(gòu)環(huán)境間遷移數(shù)據(jù)結(jié)構(gòu)、數(shù)據(jù)、function備份恢復(fù)l 用于在異構(gòu)環(huán)境間遷移數(shù)據(jù)結(jié)構(gòu)、數(shù)據(jù)、functionl Each active segment is dumped in parallell Dump files created in segment data directory by defaultl Supports compression (gzip)l Ensure sufficient disk space for dump filesl A backup set is identified by a timestamp keylExample:Back up

22、 a database: gp_dump gpdbBack up a database, and create dump files in a centralized location on all hosts: gp_dump -gp-d=/home/gpadmin/backups gpdbBack up a particular schema only: gp_dump -n myschema mydatabaseBack up a single segment instance only (by noting the dbid of the segment instance): gp_d

23、ump -gp-s=i5 gpdblOn the master host gp_catalog_1_ gp_cdatabase_1_ gp_dump_1_ gp_dump_status_1_ lOn the segment hosts gp_dump_0_gp_dump_status_0_l Use gp_restore commandl Need timestamp key from gp_dumpl Make sure dump files are placed on correct segment hostsl Make sure database exists before resto

24、ringl Database-level server configuration settings are not restoredl Examples Restore an Greenplum database using backup files created by gp_dump:gp_restore -gp-k=2005103112453 -d gpdb Restore a single segment instance only (by noting the dbid of the segment instance):gp_restore -gp-k=2005103112453

25、-d gpdb -gp-s=i5l gpcrondumpCalls to gp_dumpCan be called directly or can schedule using CRONSend email notificationsFlexible dump optionsCan copy configuration filesCan dump system catalogsCan dump global objectsCan include a post-dump scriptl gpdbrestoreRestores from gpcrondump filesCan restore fr

26、om an archive host no need to pre-place dump files on segmentsl Green plum also supports pg_dump and pg_restore l Useful for migrating data to/from other DBMSl pg_dump creates a single dump fileCan be slow on very large databasesRun at low-usage timesSupports compressionCan dump data as INSERT or CO

27、PY commandsgp-syntax option includes DISTRIBUTED BY statements in DDLl Dump a database called mydb into a SQL-script file:pg_dump mydb db.sqll To reload such a script into a (freshly created) database named newdb:psql -d newdb -f db.sqll Dump a Greenplum database in tar file format and include distr

28、ibution policy information:pg_dump -Ft -gp-syntax mydb db.tarl To dump a database into a custom-format archive file:pg_dump -Fc mydb db.dumpl To reload an archive file into a (freshly created) database named newdb:pg_restore -d newdb db.dumpl To dump a single table named mytab:pg_dump -t mytab mydb

29、db.sqll To specify an upper-case or mixed-case name in -t and related switches, you need to double-quote the name; else it will be folded to lower case. But double quotes are special to the shell, so in turn they must be quoted. Thus, to dump a single table with a mixed-case name, you need something

30、 like:pg_dump -t MixedCaseName mydb mytab.sqll pgAdmin3 圖形化管理和SQL執(zhí)行/分析/監(jiān)控工具l psql 行命令操作和管理工具l pgAdmin3 is the leading graphical Open Source management, development and administration tool for PostgreSQL Greenplum has contributed extensive GPDB-specific enhancements With GPDB 3.3, Greenplum ships and

31、 supports this tooll 監(jiān)控活動session ,同SQL：select * from pg_stat_activity;l 監(jiān)控鎖，從pg_lock中獲取信息l 可以停止正在運(yùn)行的SQLl Connect through the masterl Connection information database name (-d | PGDATABASE) master host name (-h | PGHOST) master port (-p | PGPORT) user name (-U | PGUSER)l First time connections templat

32、e1 database default superuser account (gpadmin)l Interactive modepsql mydatabasemydatabase=# SELECT * FROM foo; l Non-interactive mode (single command) psql mydatabase ac “SELECT * FROM foo;”l Non-interactive mode (multiple commands) psql mydatabase af /home/lab1/sql/createdb.sqll (Use semi-colon (;

33、) to denote end of a statement)l ? (help on psql meta-commands) l h (help on SQL command syntax)l dt (show tables) l dtS (show system tables) l dg or du (show roles) l l (show databases)l c db_name (connect to this database) l q (quit psql) l ! (Enter into shell mode)l df (show function)l dn(show sc

34、hema)l Set search_path=l timingpostgresql.confLocalLocalLocalLocall 參數(shù)參考Adminguidel 重要參數(shù):max_connection,share_buff,work_meml Local 變量的修改，如max_stack_depth需要修改所有segment上的valuel Located in master or segment instances data directoryl Used to set configuration parameters on the system levell Parameters t

35、hat are using the default setting are commented out (#)l Requires a restart (or reload using gpstop -u) for changes to take effectl View a specific parameter setting Example: SHOW search_path;l View all parameter settings Example: SHOW ALL;l Set parameter Example: set search_path=public set client_e

36、ncoding=gb18030 l 客戶端授權(quán) 是否允許從某個客戶端的連接 用戶是否可以連接到所請求的數(shù)據(jù)庫l pg_hba.conf file 基于host address, database, and/or DB user account控制權(quán)限 位于master和segment實例的數(shù)據(jù)目錄中 系統(tǒng)初始化時進(jìn)行default配置l Local connections allowed for Greenplum superuserl Remote connections not allowedl EXAMPLE# TYPE DATABASE USER CIDR-ADDRESS METHOD

37、 local all gpadmin ident sameuser local all all ident sameuser host all gpadmin /0 trust l EXAMPLE# TYPE DATABASE USER CIDR-ADDRESS METHOD localallall trust hostall all/32 trust hostall all:1/128 trust hostall all06/32 trust hostcarddwetl2/32md5 hostgpadminall21

38、.104.138.0/24md5l gpstop -u 可與在不重啟數(shù)據(jù)庫方式下，讓設(shè)置生效l 具體參考Gp sql language：l 注意事項： DELETE ,UPDATE在兩表關(guān)聯(lián)時，兩個表的distribution必須一致。 如：delete from tablea using tableb where tablea.id=tableb.idUPDATE table a as a SET desc= b.desc FROM tableb as b WHERE a.id=b.id 以上操作 table a,table b 必須使用相同的分布，必要時可以使用 alter table s

39、et distribution 進(jìn)行分布修改。l 常用數(shù)據(jù)類型 CHAR,VARCHAR,TEXT Smallint ,integer,bigint Numeric, real,double precision Timestamp,date,time Boolean Array 類型。如 integerl 其它數(shù)據(jù)類型請參考lAll system catalogs in pg_catalog schemalStandard PostgreSQL system catalogs (pg_*)lGreenplum-specific catalogs: gp_configuration gp_dis

40、tribution_policy gp_id gp_version_at_initdb pg_resqueue pg_exttable pg_tables pg_class pg_stat_activitylTo list all system catalog tables in psql: dtSlTo list all system views in psql: dvSl其它 catalog 參考 l 日期函數(shù)Extract（day|month|year。 From date);Select date + 1 day:interval,date+ 1 month:intervalSELEC

41、T date_part(day, TIMESTAMP 2001-02-16 20:38:40); Result: 16SELECT date_trunc(hour, TIMESTAMP 2001-02-16 20:38:40); Result: 2001-02-16 20:00:00 pg_sleep(seconds); 系統(tǒng)日期變量Current_dateCurrent_timeCurrent_timestampNow()Timeofday() 在 事務(wù)中發(fā)生變化，以上函數(shù)在事務(wù)中不變l 字符串處理函數(shù)Substr/length/lower/upper/trim/replace/positi

42、onrPad/lpadTo_char, | (字符串連接)substring(string from pattern/ * ，like，simillar to (模式匹配)l 其它雜類Case 。When/Coalescenullifgenerate_seriesIn/not in/exists/any/all各類函數(shù)參考：l Greenplum支持SQL/PYTHON/PERL/C語言構(gòu)建函數(shù)，以下著重介紹SQL 存儲過程。 一個存儲過程就是一個事務(wù)，包括對子過程的調(diào)用都在一個事務(wù)內(nèi) 存儲過程結(jié)構(gòu)：CREATE FUNCTION somefunc() RETURNS integer AS $

43、DECLARE quantity integer := 30;BEGIN RETURN .;END;$ LANGUAGE plpgsql; 賦值給一個變量或行/記錄賦值用下面方法：identifier := expression例子：user_id := 20; 執(zhí)行一個沒有結(jié)果的查詢: PERFORM query;一個例子：PERFORM create_mv(cs_session_page_requests_mv, my_query);存儲過程請參考：存儲過程請參考：l動態(tài)SQLEXECUTE command-string INTO STRICT target;lSELECT INTOExa

44、mple：SELECT ID INTO VAR_ID FROM TABLEAl獲取結(jié)果狀態(tài)GET DIAGNOSTICS variable = item , .;一個例子：GET DIAGNOSTICS integer_var = ROW_COUNT;lSQL返回變量SQLERRM， SQLSTATEl控制結(jié)構(gòu)IF . THEN . ELSEIF . THEN . ELSELOOP, EXIT, CONTINUE, WHILE, FOR l從函數(shù)返回有兩個命令可以用來從函數(shù)中返回數(shù)據(jù)：RETURN 和 RETURN NEXT 。Syntax：RETURN expression;l設(shè)置回調(diào)EXE

45、C SQL WHENEVER condition action; condition 可以是下列之一： SQLERROR，SQLWARNING，NOT FOUNDl異常處理EXCEPTION WHEN unique_violation THEN - do nothing END;忽略錯誤：EXCEPTION WHEN OTHERS THEN RAISE NOTICE an EXCEPTION is about to be raised; RAISE EXCEPTION NUM:%, DETAILS:%, SQLSTATE, SQLERRM;END;l錯誤和消息RAISE level forma

46、t , expression , .;Level:Info:信息輸入Notice:信息提示Exception:產(chǎn)生一個例外，將退出存儲過程Example: RAISE NOTICE Calling cs_create_job(%), v_job_id;Performance Tuningl Introduction to performance tuningl Common performance problemsl Tracking down a performance probleml Query profiling (EXPLAIN, EXPLAIN ANALYZE)l Query tu

47、ningl 我的經(jīng)驗：lSet performance expectationsacceptable response times, queries per minute, etc.BenchmarkslKnow your baseline hardware performancethroughput / capacitylKnow your workloadheavy usage timesresource contentiondata contentionlFocus your optimizationslHardware Issues / Failed SegmentslResource

48、 AllocationlContention Between Concurrent WorkloadslInaccurate Database StatisticslUneven Data DistributionlSQL FormulationlDatabase Design lDisk failureslHost failureslNetwork failureslOS not tuned for GreenplumlDisk Capacity 70% maximum recommended VACUUM after updates, deletes and loadslVACUUM co

49、nfiguration parameters max_fsm_relations = tables + indexes + system tables max_fsm_pages = 16 * max_fsm_relations l Greenplum resource queueslimit active queries in the systemlimit the size of a query a particular user can runlPerform admin tasks at low usage timesData loading, ETLVACUUM, ANALYZEBa

50、ckupslDesign applications to prevent lock conflictsConcurrent sessions not updating the same data at the same timelResource-related Configuration Parameterswork_mem = 32MBmaintenance_work_mem = 64MBshared_buffers = 125MBlDatabase statistics used by the query plannerlRun ANALYZE afterData loadsRestor

51、es from backupsChanges to schema (adding indexes, etc.)Inserts, Updates, or DeleteslCan configure statistics collection default_statistics_target = 25 gp_analyze_relative_error = .25 on specific table columnsALTER TABLE name ALTER column SET STATISTICS # lTable Distribution Key Considerations Even d

52、ata distributionLocal vs. distributed operationsEven query processing lChecking for data skewgpskew t schema.tableUnix system utilities (gpssh)：gpssh f seg_host -sar 1 100lRebalancing a Table CREATE TABLE sales_temp (LIKE sales) DISTRIBUTED BY (date, total, customer); INSERT INTO sales_temp SELECT *

53、 FROM sales; DROP sales; ALTER TABLE sales_temp RENAME TO sales; l Data Type Selectionsmallest size possible to fit data INTEGER, not NUMERIC(11,2) for integer fieldssame data type across tables for join columnsconsider hash of wide join keys, using BYTEA instead of CHAR(100) varchar or text for cha

54、racter data lDenormalization (star schema)lTable Partitioning lUse sparingly in Greenplum DatabaselTry workload without indexes firstlCan improve performance of OLTP type workloadslOther index considerations:Avoid on frequently updated columnsAvoid overlapping indexesUse bitmap indexes where applica

55、ble instead of B-treeDrop indexes for loadsConsider a clustered indexlConfiguring Index Usage:enable_indexscan = on | offlGeneral ConsiderationsKnow your dataMinimize returned rowsAvoid unnecessary columns/tables in result setAvoid large sorts if possibleMatch data types in joinslGreenplum-specific

56、ConsiderationsJoin on common distribution key columns when possibleConsider data distribution policy and query predicateslSystem Catalog Tables and Viewspg_stat_activitypg_locks / pg_classlDatabase LogsLocated in master (and segment) data directorieslUNIX system utilities (gpssh)lExamine query plans

57、 to identify tuning opportunitieslWhat to look for?Plan operations that are taking exceptionally longAre the planners estimates close to reality? (EXPLAIN ANALYZE)Is the planner applying selective predicates early?Is the planner choosing the best join order?Is the planner selectively scanning partit

58、ioned tables?Is the planner choosing hash aggregate and hash join operations where applicable? Is there sufficient work memory?lTo see the plan for a queryEXPLAIN EXPLAIN ANALYZE lQuery plans are read from bottom to topMotions (Gather, Redistribute, Broadcast)Joins, sorts, aggregationsTable scanslTh

59、e following metrics are given for each operationcost (units of disk page fetches)rows (rows output by this node)width (bytes of the rows produced by this node)EXPLAIN SELECT * FROM names WHERE name = Joelle; - QUERY PLAN -Gather Motion 2:1 (slice1) (cost=0.00.20.88 rows=1 width=13) - Seq Scan on nam

60、es (cost=0.00.20.88 rows=1 width=13) Filter: name:text Joelle:text EXPLAIN ANALYZE SELECT * FROM names WHERE name = Joelle;- QUERY PLAN -Gather Motion 2:1 (slice1) (cost=0.00.20.88 rows=1 width=13) recv: Total 1 rows with 0.305 ms to first row, 0.537 ms to end. - Seq Scan on names (cost=0.00.20.88 rows=