{"id":91903,"date":"2020-08-20T07:42:18","date_gmt":"2020-08-20T05:42:18","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/kak-bigquery-ot-google-demokratiziroval-analiz-dannyh-chast-2"},"modified":"2020-08-20T07:42:18","modified_gmt":"2020-08-20T05:42:18","slug":"kak-bigquery-ot-google-demokratiziroval-analiz-dannyh-chast-2","status":"publish","type":"post","link":"https:\/\/prohoster.info\/ro\/blog\/administrirovanie\/kak-bigquery-ot-google-demokratiziroval-analiz-dannyh-chast-2","title":{"rendered":"Cum a democratizat Google BigQuery analiza datelor. Partea 2","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><b><i>Bun\u0103, Habr! Chiar acum, OTUS a deschis \u00eenscrierea pentru noul flux al cursului <noindex><a rel=\"nofollow\" href=\"https:\/\/otus.pw\/wDZQ\/\">\u201eInginer de date\u201d<\/a><\/noindex>. \u00cen preg\u0103tirea \u00eenceperii cursului, continu\u0103m s\u0103 \u00eemp\u0103rt\u0103\u0219im cu voi materiale utile. <\/i><\/b><\/p>\n<p><i><noindex><a rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/otus\/\">Cite\u0219te prima parte<\/a><\/noindex><\/i><\/p>\n<p><img decoding=\"async\" alt=\"Cum a democratizat Google BigQuery analiza datelor. Partea 2\" src=\"\/wp-content\/uploads\/2020\/08\/7b9314bffd954cd408807280f8956c21.png\" style=\"display:block;margin: 0 auto;\" \/><\/p>\n<h4>Gestionarea datelor<\/h4>\n<p>\nGuvernan\u021ba puternic\u0103 a datelor (Strong Data Governance) este principala direc\u021bie \u00een Twitter Engineering. Pe m\u0103sur\u0103 ce implement\u0103m BigQuery \u00een platforma noastr\u0103, ne concentr\u0103m pe descoperirea datelor, controlul accesului, securitatea \u0219i confiden\u021bialitatea.<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><\/p>\n<p>Pentru descoperirea \u0219i gestionarea datelor, am extins nivelul nostru de acces la date (Data Access Layer \u2014 <noindex><a rel=\"nofollow\" href=\"https:\/\/blog.twitter.com\/engineering\/en_us\/topics\/insights\/2016\/discovery-and-consumption-of-analytics-data-at-twitter.html\">DAL<\/a><\/noindex>), pentru a oferi instrumente at\u00e2t pentru datele locale, c\u00e2t \u0219i pentru datele Google Cloud, oferind o interfa\u021b\u0103 \u0219i un API unificat pentru utilizatorii no\u0219tri. Pe m\u0103sur\u0103 ce Google <noindex><a rel=\"nofollow\" href=\"https:\/\/cloud.google.com\/data-catalog\/\">Data Catalog<\/a><\/noindex> trece spre publicare, \u00eel vom include \u00een proiectele noastre pentru a oferi utilizatorilor func\u021bii precum c\u0103utarea pe coloane.<\/p>\n<p>BigQuery faciliteaz\u0103 partajarea \u0219i accesul la date, dar trebuie s\u0103 control\u0103m acest lucru \u00eentr-o oarecare m\u0103sur\u0103 pentru a preveni exfiltrarea datelor. Printre alte instrumente, am ales dou\u0103 func\u021bii:<\/p>\n<ul>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/cloud.google.com\/resource-manager\/docs\/organization-policy\/restricting-domains\">Partajarea restric\u021bionat\u0103 pe domeniu<\/a><\/noindex>: func\u021bie beta care interzice utilizatorilor s\u0103 partajeze seturi de date BigQuery cu utilizatori din afara Twitter.<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/cloud.google.com\/vpc-service-controls\/\">Controalele serviciului VPC<\/a><\/noindex>: un control care previne exfiltrarea datelor \u0219i necesit\u0103 ca utilizatorii s\u0103 acceseze BigQuery din intervale IP cunoscute.<\/li>\n<\/ul>\n<p>\nAm implementat cerin\u021bele de autentificare, autorizare \u0219i audit (AAA) pentru a asigura securitatea \u00een modul urm\u0103tor:<\/p>\n<ul>\n<li> Autentificare: am folosit conturi de utilizator GCP pentru interog\u0103ri ad hoc \u0219i conturi de serviciu pentru solicit\u0103ri de lucru.<\/li>\n<li>Autorizare: am cerut ca fiecare set de date s\u0103 aib\u0103 un cont de serviciu proprietar \u0219i un grup de cititori.<\/li>\n<li>Audit: am exportat jurnalele stackdriver-ului BigQuery, care con\u021bineau informa\u021bii detaliate despre execu\u021bia interog\u0103rilor, \u00een seturi de date BigQuery pentru a facilita analiza.<\/li>\n<\/ul>\n<p>\nPentru a asigura o gestionare adecvat\u0103 a datelor personale ale utilizatorilor Twitter, trebuie s\u0103 \u00eenregistr\u0103m toate seturile de date BigQuery, s\u0103 adnot\u0103m datele personale, s\u0103 men\u021binem o stocare corespunz\u0103toare \u0219i s\u0103 elimin\u0103m datele care au fost \u0219terse de utilizatori.<\/p>\n<p>Am analizat Google <noindex><a rel=\"nofollow\" href=\"https:\/\/cloud.google.com\/dlp\/\">Cloud Data Loss Prevention API<\/a><\/noindex>, care utilizeaz\u0103 \u00eenv\u0103\u021barea automat\u0103 pentru clasificarea \u0219i editarea datelor sensibile, dar am decis \u00een favoarea anot\u0103rii manuale a setului de date din cauza acurate\u021bei. Pl\u0103nuim s\u0103 utiliz\u0103m API-ul de Prevenire a Pierderii Datelor pentru a completa anotarea realizat\u0103 de utilizatori.<\/p>\n<p>\u00cen Twitter, am creat patru categorii de confiden\u021bialitate pentru seturile de date din BigQuery, enumerate aici \u00een ordinea descresc\u0103toare a sensibilit\u0103\u021bii:<\/p>\n<ul>\n<li>Seturile de date cu sensibiltate ridicat\u0103 sunt disponibile dup\u0103 nevoie, baz\u00e2ndu-ne pe principiul privilegiilor minime. Fiecare set de date are un grup separat de cititori, iar noi vom urm\u0103ri utilizarea conturilor individuale.<\/li>\n<li>Seturile de date cu sensibilitate medie (pseudonime unidirec\u021bionale folosind hashing cu sare) nu con\u021bin informa\u021bii personale identificabile (Personally Identifiable Information \u2014 PII) \u0219i sunt disponibile pentru un grup mai mare de angaja\u021bi. Aceasta este o bun\u0103 balan\u021b\u0103 \u00eentre considera\u021biile de confiden\u021bialitate \u0219i utilitatea datelor. Permite angaja\u021bilor s\u0103 efectueze sarcini de analiz\u0103, cum ar fi calcularea num\u0103rului de utilizatori care au folosit func\u021bia, f\u0103r\u0103 a \u0219ti cine sunt utilizatorii reali.<\/li>\n<li>Seturile de date cu sensibilitate sc\u0103zut\u0103 includ toate informa\u021biile care identific\u0103 utilizatorul. Aceasta este o abordare bun\u0103 din punct de vedere al confiden\u021bialit\u0103\u021bii, dar nu poate fi utilizat\u0103 pentru analize la nivel de utilizator.<\/li>\n<li>Seturile de date publice (emise \u00een afara Twitter) sunt disponibile tuturor angaja\u021bilor Twitter.<\/li>\n<\/ul>\n<p>\n\u00cen ceea ce prive\u0219te \u00eenregistrarea, am folosit sarcini programate pentru a enumera seturile de date BigQuery \u0219i pentru a le \u00eenregistra \u00een Data Access Layer (<noindex><a rel=\"nofollow\" href=\"https:\/\/blog.twitter.com\/engineering\/en_us\/topics\/insights\/2016\/discovery-and-consumption-of-analytics-data-at-twitter.html\">DAL<\/a><\/noindex>), depozitul de metadate Twitter. Utilizatorii vor anota seturile de date cu informa\u021bii despre confiden\u021bialitate, precum \u0219i vor specifica durata de p\u0103strare. \u00cen ceea ce prive\u0219te cur\u0103\u021barea, evalu\u0103m performan\u021ba \u0219i costul a dou\u0103 op\u021biuni: <i>1.<\/i> Cur\u0103\u021barea seturilor de date \u00een GCS cu ajutorul unor instrumente precum Scalding \u0219i \u00eenc\u0103rcarea acestora \u00een BigQuery; <i>2.<\/i> Utilizarea operatorilor BigQuery DML. Probabil c\u0103 vom utiliza o combina\u021bie a ambelor metode pentru a satisface cerin\u021bele diferitelor grupuri \u0219i date.<\/p>\n<h4>Func\u021bionalitatea sistemului<\/h4>\n<p>\nDeoarece BigQuery este un serviciu gestionat, nu a fost necesar\u0103 implicarea echipei SRE de la Twitter \u00een gestionarea sistemelor sau \u00eendeplinirea sarcinilor de gard\u0103. A fost u\u0219or s\u0103 asigur\u0103m o capacitate mare at\u00e2t pentru stocare, c\u00e2t \u0219i pentru calcule. Am putea ajusta rezerv\u0103rile de sloturi, cre\u00e2nd tichete \u00een suportul Google. Am stabilit c\u0103 ar fi posibil s\u0103 \u00eembun\u0103t\u0103\u021bim, de exemplu, auto-serviciul pentru distribuirea sloturilor \u0219i s\u0103 \u00eembun\u0103t\u0103\u021bim tabloul de bord pentru monitorizare \u0219i am transmis aceste solicit\u0103ri Google.<\/p>\n<h4>Pre\u021b<\/h4>\n<p>\nAnaliza noastr\u0103 preliminar\u0103 a ar\u0103tat c\u0103 costul interog\u0103rilor pentru BigQuery \u0219i Presto era similar. Am achizi\u021bionat sloturi la <noindex><a rel=\"nofollow\" href=\"https:\/\/cloud.google.com\/bigquery\/pricing#flat_rate_pricing\">pre\u021b fix<\/a><\/noindex> pentru a avea un cost lunar stabil \u00een loc de a pl\u0103ti <noindex><a rel=\"nofollow\" href=\"https:\/\/cloud.google.com\/bigquery\/pricing#on_demand_pricing\">la cerere<\/a><\/noindex> pe TB de date prelucrate. Aceast\u0103 decizie a fost, de asemenea, bazat\u0103 pe feedbackul utilizatorilor care nu doreau s\u0103 se g\u00e2ndeasc\u0103 la costurile asociate cu fiecare interogare.<\/p>\n<p>Stocarea datelor \u00een BigQuery a generat costuri suplimentare pe l\u00e2ng\u0103 cheltuielile cu GCS. Instrumente precum Scalding necesit\u0103 seturi de date \u00een GCS, iar pentru a accesa BigQuery a trebuit s\u0103 \u00eenc\u0103rc\u0103m acelea\u0219i seturi de date \u00een formatul BigQuery <noindex><a rel=\"nofollow\" href=\"https:\/\/cloud.google.com\/blog\/products\/gcp\/inside-capacitor-bigquerys-next-generation-columnar-storage-format\">Capacitor<\/a><\/noindex>. Lucr\u0103m la conectarea Scalding-ului cu seturile de date BigQuery, ceea ce va elimina necesitatea stoc\u0103rii seturilor de date at\u00e2t \u00een GCS, c\u00e2t \u0219i \u00een BigQuery.<\/p>\n<p>Pentru cazurile rare care necesitau interog\u0103ri ocazionale pe zeci de petabytes, am decis c\u0103 stocarea seturilor de date \u00een BigQuery nu este rentabil\u0103 \u0219i am folosit Presto pentru accesul direct la seturile de date din GCS. \u00cen acest scop, ne uit\u0103m la Sursele de Date Externe BigQuery.<\/p>\n<h3>Urm\u0103torii pa\u0219i<\/h3>\n<p>\nAm observat un interes mare pentru BigQuery \u00eenc\u0103 de la lansarea versiunii alpha. Ad\u0103ug\u0103m mai multe seturi de date \u0219i mai multe echipe \u00een BigQuery. Dezvolt\u0103m conectori pentru instrumente de analiz\u0103 a datelor, cum ar fi Scalding, pentru a citi \u0219i a scrie \u00een stocarea BigQuery. Lu\u0103m \u00een considerare instrumente precum Looker \u0219i Apache Zeppelin pentru a crea rapoarte corporative despre calitate \u0219i note folosind seturi de date BigQuery.<\/p>\n<p>Colaborarea cu Google a fost foarte productiv\u0103 \u0219i suntem \u00eenc\u00e2nta\u021bi s\u0103 continu\u0103m \u0219i s\u0103 dezvolt\u0103m acest parteneriat. Am colaborat cu Google pentru a implementa propriul nostru <noindex><a rel=\"nofollow\" href=\"https:\/\/developers.google.com\/issue-tracker\/guides\/partner-access\">Partener Issue Tracker<\/a><\/noindex>, pentru a trimite solicit\u0103ri direct c\u0103tre Google. Unele dintre acestea, cum ar fi \u00eenc\u0103rc\u0103torul Parquet BigQuery, sunt deja implementate de Google.<\/p>\n<p>Iat\u0103 c\u00e2teva dintre cele mai importante solicit\u0103ri de func\u021bionalitate pentru Google:<\/p>\n<ul>\n<li>Instrumente pentru primirea u\u0219oar\u0103 a datelor \u0219i suport pentru formatul LZO-Thrift.<\/li>\n<li>Segmentare pe or\u0103<\/li>\n<li>\u00cembun\u0103t\u0103\u021biri \u00een domeniul controlului accesului, cum ar fi permisiuni la nivel de tabele, r\u00e2nduri \u0219i coloane.<\/li>\n<li>BigQuery <noindex><a rel=\"nofollow\" href=\"https:\/\/cloud.google.com\/bigquery\/external-data-sources\">Surse externe de date<\/a><\/noindex> cu integrarea \u0219i suportul Hive Metastore pentru formatul LZO-Thrift.<\/li>\n<li>Integrare \u00eembun\u0103t\u0103\u021bit\u0103 a catalogului de date \u00een interfa\u021ba utilizatorului BigQuery<\/li>\n<li>Auto-servire pentru distribuirea \u0219i monitorizarea sloturilor.<\/li>\n<\/ul>\n<p><\/p>\n<h3>Concluzie<\/h3>\n<p>\nDemocratizarea analizei datelor, vizualiz\u0103rii \u0219i \u00eenv\u0103\u021b\u0103rii automate \u00eentr-un mod sigur este o prioritate de rang \u00eenalt pentru echipa Data Platform. Am identificat Google BigQuery \u0219i Data Studio ca instrumente care pot ajuta la atingerea acestui obiectiv \u0219i am lansat anul trecut BigQuery Alpha pentru \u00eentreaga companie. <\/p>\n<p>Am constatat c\u0103 interog\u0103rile \u00een BigQuery au fost simple \u0219i eficiente. Pentru primirea \u0219i transformarea datelor, am folosit instrumentele Google pentru conducte simple, dar pentru conducte complexe a trebuit s\u0103 ne construim propria infrastructur\u0103 Airflow. \u00cen domeniul gestion\u0103rii datelor, serviciile BigQuery pentru autentificare, autorizare \u0219i audit \u00eendeplinesc nevoile noastre. Pentru gestionarea metadatelor \u0219i asigurarea confiden\u021bialit\u0103\u021bii, aveam nevoie de o flexibilitate mai mare \u0219i a fost necesar s\u0103 construim propriile sisteme. BigQuery, fiind un serviciu gestionat, a fost u\u0219or de utilizat. Costurile interog\u0103rilor au fost similare cu cele ale instrumentelor existente. Stocarea datelor \u00een BigQuery a adus cheltuieli suplimentare pe l\u00e2ng\u0103 costurile pentru GCS.<\/p>\n<p>\u00cen general, BigQuery func\u021bioneaz\u0103 bine pentru analiza SQL general\u0103. Observ\u0103m un interes mare pentru BigQuery \u0219i lucr\u0103m la mutarea unui num\u0103r mai mare de seturi de date, atragerea unui num\u0103r mai mare de echipe \u0219i crearea unui num\u0103r mai mare de conducte cu BigQuery. \u00cen Twitter se folosesc date variate, pentru care va fi necesar un amestec de instrumente precum Scalding, Spark, Presto \u0219i Druid. Inten\u021bion\u0103m s\u0103 continu\u0103m s\u0103 ne dezvolt\u0103m instrumentele de analiz\u0103 a datelor \u0219i s\u0103 oferim recomand\u0103ri clare utilizatorilor no\u0219tri despre cum s\u0103 foloseasc\u0103 cel mai bine oferte noastre.<\/p>\n<h3>Cuvinte de mul\u021bumire<\/h3>\n<p>\nA\u0219 dori s\u0103 le mul\u021bumesc colegilor \u0219i colaboratorilor mei, Anju Dja \u0219i Will Pascucci, pentru colaborarea lor excelent\u0103 \u0219i munca asidu\u0103 la acest proiect. De asemenea, a\u0219 dori s\u0103 le mul\u021bumesc inginerilor \u0219i managerilor din mai multe echipe de la Twitter \u0219i Google, care ne-au ajutat pe noi \u0219i utilizatorii BigQuery de la Twitter, oferindu-ne feedback valoros.<\/p>\n<p>Dac\u0103 e\u0219ti interesat s\u0103 lucrezi la aceste sarcini, consult\u0103 <noindex><a rel=\"nofollow\" href=\"https:\/\/careers.twitter.com\/content\/careers-twitter\/en\/jobs-search.html?q=&amp;team=careers-twitter%3Ateam%2Finfrastructure-engineering\">job postings<\/a><\/noindex> echipa Data Platform.<\/p>\n<p>\n<noindex><a rel=\"nofollow\" href=\"https:\/\/otus.pw\/eD9S\/\">Calitatea datelor \u00een DWH - consisten\u021ba depozitului de date<\/a><\/noindex><\/p>\n<p>Sursa: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/otus\/blog\/513782\/\">habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041f\u0440\u0438\u0432\u0435\u0442, \u0425\u0430\u0431\u0440! \u041f\u0440\u044f\u043c\u043e \u0441\u0435\u0439\u0447\u0430\u0441 \u0432 OTUS \u043e\u0442\u043a\u0440\u044b\u0442 \u043d\u0430\u0431\u043e\u0440 \u043d\u0430 \u043d\u043e\u0432\u044b\u0439 \u043f\u043e\u0442\u043e\u043a \u043a\u0443\u0440\u0441\u0430 \u00abData Engineer\u00bb. \u0412 \u043f\u0440\u0435\u0434\u0434\u0432\u0435\u0440\u0438\u0438 \u0441\u0442\u0430\u0440\u0442\u0430 \u043a\u0443\u0440\u0441\u0430 \u043f\u0440\u043e\u0434\u043e\u043b\u0436\u0430\u0435\u043c \u0434\u0435\u043b\u0438\u0442\u044c\u0441\u044f \u0441 \u0432\u0430\u043c\u0438 \u043f\u043e\u043b\u0435\u0437\u043d\u044b\u043c \u043c\u0430\u0442\u0435\u0440\u0438\u0430\u043b\u043e\u043c. \u0427\u0438\u0442\u0430\u0442\u044c \u043f\u0435\u0440\u0432\u0443\u044e \u0447\u0430\u0441\u0442\u044c \u0423\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0434\u0430\u043d\u043d\u044b\u043c\u0438 \u0421\u0438\u043b\u044c\u043d\u043e\u0435 \u0443\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0434\u0430\u043d\u043d\u044b\u043c\u0438 (Strong Data Governance) \u2014 \u043e\u0441\u043d\u043e\u0432\u043d\u043e\u0439 \u043f\u0440\u0438\u043d\u0446\u0438\u043f Twitter Engineering. \u041f\u043e\u0441\u043a\u043e\u043b\u044c\u043a\u0443 \u043c\u044b \u0432\u043d\u0435\u0434\u0440\u044f\u0435\u043c BigQuery \u0432 \u043d\u0430\u0448\u0443 \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u0443, \u043c\u044b \u043a\u043e\u043d\u0446\u0435\u043d\u0442\u0440\u0438\u0440\u0443\u0435\u043c\u0441\u044f \u043d\u0430 \u043e\u0431\u043d\u0430\u0440\u0443\u0436\u0435\u043d\u0438\u0438 \u0434\u0430\u043d\u043d\u044b\u0445, \u043a\u043e\u043d\u0442\u0440\u043e\u043b\u0435 \u0434\u043e\u0441\u0442\u0443\u043f\u0430, \u0431\u0435\u0437\u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u0438 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":91904,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-91903","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041f\u0440\u0438\u0432\u0435\u0442, \u0425\u0430\u0431\u0440! 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