{"id":66980,"date":"2021-06-09T09:16:46","date_gmt":"2021-06-09T08:16:46","guid":{"rendered":"https:\/\/datascientest.com\/?p=66980"},"modified":"2023-11-09T14:07:10","modified_gmt":"2023-11-09T14:07:10","slug":"apache-pig","status":"publish","type":"post","link":"https:\/\/datascientest.com\/apache-pig","title":{"rendered":"Apache Pig : tout savoir sur le langage de programmation d&rsquo;Hadoop"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"66980\" class=\"elementor elementor-66980\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8677bc9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8677bc9\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-29dedfc\" data-id=\"29dedfc\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-819c92e elementor-widget elementor-widget-heading\" data-id=\"819c92e\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\">Apache Pig est le langage de programmation permettant d'utiliser Hadoop et MapReduce. D\u00e9couvrez tout ce que vous devez savoir : pr\u00e9sentation, cas d'usage, avantage, formations...<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5a688d7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5a688d7\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d6a11a3\" data-id=\"d6a11a3\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-34f0ed5 elementor-widget elementor-widget-text-editor\" data-id=\"34f0ed5\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>Le mod\u00e8le de programmation MapReduce du framework Apache Hadoop permet de traiter de larges volumes de donn\u00e9es Big Data. Toutefois, les Data Analysts ne ma\u00eetrisent pas toujours ce paradigme. C&rsquo;est la raison pour laquelle <strong>une abstraction appel\u00e9e Pig a \u00e9t\u00e9 ajout\u00e9e \u00e0 Hadoop<\/strong>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-36ad063 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"36ad063\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-048cf20\" data-id=\"048cf20\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6026293 elementor-widget elementor-widget-heading\" data-id=\"6026293\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Qu'est-ce que Apache Pig ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8ea3513 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8ea3513\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-0a98a8a\" data-id=\"0a98a8a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1c28183 elementor-widget elementor-widget-text-editor\" data-id=\"1c28183\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Le langage de programmation de haut niveau Apache Pig est tr\u00e8s utile pour analyser de larges ensembles de donn\u00e9es. Il fut <strong>initialement d\u00e9velopp\u00e9 en interne par Yahoo !<\/strong> en 2006, dans le but de cr\u00e9er et d&rsquo;ex\u00e9cuter des jobs MapReduce sur tous les datasets.<\/p><p>Le nom \u00a0\u00bb Pig \u00a0\u00bb a \u00e9t\u00e9 choisi, car ce langage de programmation est con\u00e7u pour fonctionner sur n&rsquo;importe quel type de donn\u00e9es <strong>\u00e0 l&rsquo;instar d&rsquo;un cochon qui d\u00e9vore tout et n&rsquo;importe quoi<\/strong>.<\/p><p>En 2007, <strong>Pig est rendu Open Source <\/strong>par le biais de l&rsquo;incubateur Apache. En 2008, la premi\u00e8re version de Apache Pig est lanc\u00e9e. Le succ\u00e8s est au rendez-vous, et Pig devient un projet Apache de premier niveau en 2010.<\/p><p>En utilisant Apache Pig, les Data Analysts peuvent passer moins de temps \u00e0 \u00e9crire des programmes MapReduce. Ils peuvent ainsi <strong>rester focalis\u00e9s sur l&rsquo;analyse<\/strong> d&rsquo;ensembles de donn\u00e9es.<\/p><p>Ainsi,<strong> Apache Pig est une abstraction pour MapReduce<\/strong>. Cet outil est utilis\u00e9 pour analyser les vastes datasets en les repr\u00e9sentant comme des flux de donn\u00e9es. Toutes les op\u00e9rations de manipulation de donn\u00e9es sur Hadoop peuvent \u00eatre effectu\u00e9es en utilisant Apache Pig.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-12f0ddf elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"12f0ddf\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a4015f4\" data-id=\"a4015f4\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-721490c elementor-widget elementor-widget-video\" data-id=\"721490c\" data-element_type=\"widget\" data-settings=\"{&quot;youtube_url&quot;:&quot;https:\\\/\\\/youtu.be\\\/OoEpfb6yga8&quot;,&quot;video_type&quot;:&quot;youtube&quot;,&quot;controls&quot;:&quot;yes&quot;}\" data-widget_type=\"video.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-video .elementor-widget-container{overflow:hidden;transform:translateZ(0)}.elementor-widget-video .elementor-wrapper{aspect-ratio:var(--video-aspect-ratio)}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{height:100%;width:100%;display:flex;border:none;background-color:#000}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-wrapper{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-wrapper iframe,.elementor-widget-video .elementor-wrapper video{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .elementor-open-inline .elementor-custom-embed-image-overlay{position:absolute;top:0;right:0;bottom:0;left:0;background-size:cover;background-position:50%}.elementor-widget-video .elementor-custom-embed-image-overlay{cursor:pointer;text-align:center}.elementor-widget-video .elementor-custom-embed-image-overlay:hover .elementor-custom-embed-play i{opacity:1}.elementor-widget-video .elementor-custom-embed-image-overlay img{display:block;width:100%;aspect-ratio:var(--video-aspect-ratio);-o-object-fit:cover;object-fit:cover;-o-object-position:center center;object-position:center center}@supports not (aspect-ratio:1\/1){.elementor-widget-video .elementor-custom-embed-image-overlay{position:relative;overflow:hidden;height:0;padding-bottom:calc(100% \/ var(--video-aspect-ratio))}.elementor-widget-video .elementor-custom-embed-image-overlay img{position:absolute;top:0;right:0;bottom:0;left:0}}.elementor-widget-video .e-hosted-video .elementor-video{-o-object-fit:cover;object-fit:cover}.e-con-inner>.elementor-widget-video,.e-con>.elementor-widget-video{width:var(--container-widget-width);--flex-grow:var(--container-widget-flex-grow)}<\/style>\t\t<div class=\"elementor-wrapper elementor-open-inline\">\n\t\t\t<div class=\"elementor-video\"><\/div>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3db03b9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3db03b9\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a622756\" data-id=\"a622756\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2e1724f elementor-widget elementor-widget-heading\" data-id=\"2e1724f\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">L'architecture Apache Pig<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3cded93 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3cded93\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-b2edc58\" data-id=\"b2edc58\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d356747 elementor-widget elementor-widget-text-editor\" data-id=\"d356747\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>L&rsquo;architecture <strong>Apache Pig repose sur deux composants principaux<\/strong> : le langage Pig Latin et l&rsquo;environnement runtime permettant l&rsquo;ex\u00e9cution des programmes PigLatin.<\/p><p>Le langage Pig Latin permet<strong> d&rsquo;\u00e9crire des programmes d&rsquo;analyse de donn\u00e9es<\/strong>. Il d\u00e9livre divers op\u00e9rateurs que les programmeurs peuvent utiliser pour d\u00e9velopper leurs propres fonctions pour lire, \u00e9crire ou traiter des donn\u00e9es.<\/p><p>Un<strong> programme Pig Latin est compos\u00e9 d&rsquo;une s\u00e9rie de transformations<\/strong> ou d&rsquo;op\u00e9rations, appliqu\u00e9es aux donn\u00e9es \u00a0\u00bb input \u00a0\u00bb (entr\u00e9e) pour produire un \u00a0\u00bb output\u00a0 \u00ab\u00a0. Ces op\u00e9rations d\u00e9crivent un flux de donn\u00e9es traduit en une repr\u00e9sentation ex\u00e9cutable par l&rsquo;environnement d&rsquo;ex\u00e9cution Hadoop Pig.<\/p><p>Pour analyser des donn\u00e9es en utilisant Apache Pig, les programmeurs doivent imp\u00e9rativement<strong> \u00e9crire des scripts avec le langage Pig Latin<\/strong>. Tous ces scripts sont convertis en t\u00e2ches Map et Reduce de fa\u00e7on interne. Le composant Pig Engine se charge de convertir les scripts en jobs MapReduce.<\/p><p>Toutefois, <strong>le programmeur n&rsquo;a m\u00eame pas connaissance de ces jobs<\/strong>. C&rsquo;est ainsi que Pig permet aux programmeurs de se concentrer sur les donn\u00e9es plut\u00f4t que sur la nature de l&rsquo;ex\u00e9cution.<\/p><p>On distingue<strong> deux modes d&rsquo;ex\u00e9cution pour Pig<\/strong>. Le mode Local s&rsquo;ex\u00e9cute sur un JVM unique et utilise le syst\u00e8me de fichier local. Ce mode est adapt\u00e9 pour l&rsquo;analyse de petits ensembles de donn\u00e9es.<\/p><p>En mode Map Reduce, <strong>les requ\u00eates \u00e9crites en Pig Latin sont traduites en jobs MapReduce<\/strong> et ex\u00e9cut\u00e9es sur un cluster Hadoop. Ce dernier peut \u00eatre partiellement ou enti\u00e8rement distribu\u00e9. Le mode MapReduce combin\u00e9 avec un cluster enti\u00e8rement distribu\u00e9 est utile pour ex\u00e9cuter Pig sur de larges ensembles de donn\u00e9es.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-a050376 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a050376\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5043503\" data-id=\"5043503\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-57b9305 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"57b9305\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data-engineer\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Suivre une formation Apache Pig<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-b4888ca elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b4888ca\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f45e0fe\" data-id=\"f45e0fe\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d46ddab elementor-widget elementor-widget-heading\" data-id=\"d46ddab\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Pourquoi utiliser Apache Pig ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-c90c1b6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c90c1b6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-6f33c45\" data-id=\"6f33c45\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d478d86 elementor-widget elementor-widget-text-editor\" data-id=\"d478d86\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Par le pass\u00e9, les programmeurs ne ma\u00eetrisant pas Java avaient du mal \u00e0 utiliser Hadoop. Il \u00e9tait particuli\u00e8rement <strong>d\u00e9licat pour eux d&rsquo;effectuer des t\u00e2ches MapReduce<\/strong>.<\/p><p>Ce probl\u00e8me a pu \u00eatre r\u00e9solu gr\u00e2ce \u00e0 Apache Pig. En utilisant le langage Pig Latin, les programmeurs peuvent effectuer facilement des t\u00e2ches MapReduce<strong> sans avoir \u00e0 taper des codes complexes en Java<\/strong>.<\/p><p>Par ailleurs, <strong>Apache Pig repose sur une approche \u00a0\u00bb multi-requ\u00eate \u00ab\u00a0<\/strong> permettant de r\u00e9duire la longueur des codes. Une op\u00e9ration qui n\u00e9cessiterait 200 lignes de code en Java peut \u00eatre r\u00e9duire \u00e0 seulement 10 linges avec Pig. En moyenne, Apache Pig divise le temps de d\u00e9veloppement par 16.<\/p><p>Un avantage du langage Pig Latin est qu&rsquo;il est<strong> relativement proche du langage SQL<\/strong>. Une personne accoutum\u00e9e \u00e0 SQL ma\u00eetrisera facilement Pig.<\/p><p>Enfin, <strong>de nombreux op\u00e9rateurs sont fournis nativement<\/strong>. Ils permettent de prendre en charge les diverses op\u00e9rations de donn\u00e9es. L&rsquo;outil offre aussi des types de donn\u00e9es comme les tuples, les bags et les maps manquant \u00e0 MapReduce.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-abbda42 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"abbda42\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-19f873c\" data-id=\"19f873c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5a97a52 elementor-widget elementor-widget-heading\" data-id=\"5a97a52\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Les applications de Apache Pig<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-056f838 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"056f838\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-871a527\" data-id=\"871a527\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-c45f39e elementor-widget elementor-widget-text-editor\" data-id=\"c45f39e\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>En r\u00e8gle g\u00e9n\u00e9rale, <strong>Apache Pig est utilis\u00e9 par les Data Scientists<\/strong> pour effectuer des t\u00e2ches impliquant le traitement Hadoop et le prototypage rapide. On l&rsquo;utilise notamment pour traiter d&rsquo;immenses sources de donn\u00e9es comme les logs web.<\/p><p>Cet outil permet aussi le traitement de donn\u00e9es pour les plateformes de recherche. Enfin, il permet de traiter <strong>les charges de donn\u00e9es sensibles au temps<\/strong>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-046602e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"046602e\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-9322484\" data-id=\"9322484\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-01991c2 elementor-widget elementor-widget-heading\" data-id=\"01991c2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Les caract\u00e9ristiques et points forts de Apache Pig<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1f3ab5c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1f3ab5c\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-33a3f5a\" data-id=\"33a3f5a\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-79aac4c elementor-widget elementor-widget-text-editor\" data-id=\"79aac4c\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Voici les principales caract\u00e9ristiques et fonctionnalit\u00e9s Apache Pig. Le langage de programmation P\u00efg Latin, <strong>similaire \u00e0 SQL<\/strong>, permet d&rsquo;\u00e9crire un script Pig facilement.<\/p><p>Un <strong>vaste ensemble d&rsquo;op\u00e9rateurs permet d&rsquo;effectuer une large vari\u00e9t\u00e9<\/strong> d&rsquo;op\u00e9rations de donn\u00e9es. \u00c0 partir de ces op\u00e9rateurs, les utilisateurs peuvent d\u00e9velopper leurs propres fonctions pour lire, traiter et \u00e9crire les donn\u00e9es.<\/p><p>Il est <strong>aussi possible de cr\u00e9er des UDF (user-defined functions)<\/strong> ou fonctions d\u00e9finies par l&rsquo;utilisateur dans d&rsquo;autres langages de programmation comme Java. Elles peuvent ensuite \u00eatre invoqu\u00e9es ou int\u00e9gr\u00e9es \u00e0 des scripts Pig.<\/p><p>En outre, les t\u00e2ches Apache Pig <strong>optimisent automatiquement leur ex\u00e9cution<\/strong>. Les programmeurs peuvent donc se focaliser uniquement sur la s\u00e9mantique du langage.<\/p><p>Avec Apache Pig, il est <strong>possible d&rsquo;analyser tous les types de donn\u00e9es<\/strong> structur\u00e9s ou non. Les r\u00e9sultats des analyses sont stock\u00e9s dans le HDFS de Apache Hadoop.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c214e14 elementor-widget elementor-widget-image\" data-id=\"c214e14\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/sche\u0301ma_hadoop-116-1024x562.png\" class=\"attachment-large size-large wp-image-76219\" alt=\"sche\u0301ma hadoop\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/sche\u0301ma_hadoop-116-1024x562.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/sche\u0301ma_hadoop-116-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/sche\u0301ma_hadoop-116-768x422.png 768w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/sche\u0301ma_hadoop-116-1536x843.png 1536w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/sche\u0301ma_hadoop-116-2048x1124.png 2048w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-5b9d086 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"5b9d086\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-27a1935\" data-id=\"27a1935\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-79e192e elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"79e192e\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data-engineer\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Apprendre \u00e0 utiliser Apache Pig<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-b4ef8f8 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b4ef8f8\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-6099c8c\" data-id=\"6099c8c\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-e9cf3e9 elementor-widget elementor-widget-heading\" data-id=\"e9cf3e9\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Apache Pig vs MapReduce<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0b36dc5 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0b36dc5\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-1c8a51b\" data-id=\"1c8a51b\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-61baf61 elementor-widget elementor-widget-text-editor\" data-id=\"61baf61\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Il existe <strong>plusieurs diff\u00e9rences majeures<\/strong> entre Apache Pig et MapReduce. Tout d&rsquo;abord, MapReduce est un paradigme de traitement de donn\u00e9es tandis que Pig est un langage de flux de donn\u00e9es.<\/p><p>C&rsquo;est <strong>un langage de haut niveau<\/strong>, alors que MapReduce est de bas niveau. Il est difficile d&rsquo;effectuer une op\u00e9ration de Joint entre des datasets avec MapReduce, alors que c&rsquo;est une t\u00e2che facile avec Pig.<\/p><p>N&rsquo;importe quel programmeur disposant de notions en SQL peut travailler avec Apache Pig, tandis que <strong>MapReduce requiert la ma\u00eetrise du Java<\/strong>.<\/p><p>Une autre diff\u00e9rence concerne <strong>la longueur des lignes de code<\/strong>. Gr\u00e2ce \u00e0 son approche multi-requ\u00eate, Apache Pig requiert 20 fois moins de lignes que MapReduce pour effectuer une m\u00eame t\u00e2che.<\/p><p>Enfin, les t\u00e2ches Mapreduce impliquent<strong> un long processus de compilation<\/strong>. Il n&rsquo;y a pas besoin de compilation avec Pig, car chaque op\u00e9rateur est converti en interne en job MapReduce \u00e0 l&rsquo;ex\u00e9cution.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-70d4876 elementor-widget elementor-widget-image\" data-id=\"70d4876\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"800\" height=\"439\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/illu_schema_mapreduce-04.png\" class=\"attachment-large size-large wp-image-74773\" alt=\"\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/illu_schema_mapreduce-04.png 1024w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/illu_schema_mapreduce-04-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/illu_schema_mapreduce-04-768x422.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-f0201cd elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"f0201cd\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ffa1ecf\" data-id=\"ffa1ecf\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-7eb99ce elementor-widget elementor-widget-heading\" data-id=\"7eb99ce\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Apache Pig vs SQL<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7d900bd elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7d900bd\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-5d20bf4\" data-id=\"5d20bf4\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2f72066 elementor-widget elementor-widget-text-editor\" data-id=\"2f72066\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Apache Pig pr\u00e9sente des similitudes avec SQL, mais aussi des diff\u00e9rences. Alors que Pig Latin est un langage proc\u00e9dural, <strong>SQL est un langage d\u00e9claratif<\/strong>.<\/p><p>En outre, <strong>un sch\u00e9ma est obligatoire en SQL<\/strong> alors qu&rsquo;il est optionnel avec Pig. Il est possible de stocker des donn\u00e9es sans concevoir de sch\u00e9ma.<\/p><p>Il y a davantage d&rsquo;opportunit\u00e9s d&rsquo;optimisation de requ\u00eate avec SQL, alors qu&rsquo;elles sont plus limit\u00e9es avec Pig. Par ailleurs, <strong>Pig Latin permet de d\u00e9composer un pipeline<\/strong>, de stocker des donn\u00e9es n&rsquo;importe o\u00f9 dans le pipeline et permet d&rsquo;effectuer des fonctions ETL (Extraction, Transformation, Chargement).<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-b421b22 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"b421b22\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f89feeb\" data-id=\"f89feeb\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-2069fee elementor-widget elementor-widget-heading\" data-id=\"2069fee\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Apache Pig vs Hive<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7e3b41d elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7e3b41d\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d86e875\" data-id=\"d86e875\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-efe8942 elementor-widget elementor-widget-image\" data-id=\"efe8942\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"300\" height=\"165\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/illu_hive_blog-01-removebg-preview-300x165.png\" class=\"attachment-medium size-medium wp-image-74758\" alt=\"Apache Hive\" srcset=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/illu_hive_blog-01-removebg-preview-300x165.png 300w, https:\/\/datascientest.com\/wp-content\/uploads\/2021\/06\/illu_hive_blog-01-removebg-preview.png 674w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-86c0320 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"86c0320\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-6745d90\" data-id=\"6745d90\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ecf11d5 elementor-widget elementor-widget-text-editor\" data-id=\"ecf11d5\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><span style=\"font-size: 15px;\">Apache Pig fut cr\u00e9\u00e9 par Yahoo, et Hive par Facebook. Le premier utilise le langage Pig Latin, le second le langage HiveQL.\u200b<\/span><\/p><p>Alors que Pig Latin est un langage de flux de donn\u00e9es et un langage proc\u00e9dural. <span style=\"font-size: 15px;\"><strong>HiveQL est un langage de traitement de requ\u00eate et<\/strong><\/span><span style=\"font-size: 15px;\">\u00a0un langage d\u00e9claratif.<\/span><\/p><p>Enfin, <strong><a href=\"https:\/\/datascientest.com\/apache-hive\">Hive<\/a> prend principalement en charge des donn\u00e9es structur\u00e9es<\/strong>. De son c\u00f4t\u00e9, Pig peut prendre en charge les donn\u00e9es structur\u00e9es, non structur\u00e9es et semi-structur\u00e9es.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-a6f5d61 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"a6f5d61\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-3f9d288\" data-id=\"3f9d288\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-8e5f229 elementor-widget elementor-widget-heading\" data-id=\"8e5f229\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Comment apprendre \u00e0 utiliser Apache Pig ?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-8426ae6 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"8426ae6\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-49eb598\" data-id=\"49eb598\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-90082ba elementor-widget elementor-widget-text-editor\" data-id=\"90082ba\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Alors que de plus en plus d&rsquo;entreprises utilisent le Big Data, la ma\u00eetrise d&rsquo;Apache Pig est<strong> une comp\u00e9tence tr\u00e8s recherch\u00e9e<\/strong>. Elle est tr\u00e8s utile pour traiter et analyser facilement de larges ensembles de donn\u00e9es avec Hadoop.<\/p><p>Pour apprendre \u00e0 manier cet outil, vous pouvez choisir <a href=\"https:\/\/datascientest.com\/formations-data\" target=\"_blank\" rel=\"noopener\">les formations DataScientest<\/a>. Le framework Apache Hadoop, et ses diff\u00e9rents composants comme Pig, Hive, Spark et HBase sont au programme du module Big Data Volume de la formation Data Engineer.<\/p><p>Les autres modules de ce parcours sont la programmation, les bases de donn\u00e9es, l&rsquo;automatisation et le d\u00e9ploiement. \u00c0 l&rsquo;issue de ce parcours, vous aurez <strong>toutes les comp\u00e9tences pour travailler<\/strong> en tant qu&rsquo;ing\u00e9nieur des donn\u00e9es.<\/p><p>Toutes nos formations sont propos\u00e9es <strong>en Formation Continue, ou en bootcamp<\/strong>. Notre approche innovante de \u00a0\u00bb Blended Learning \u00a0\u00bb allie apprentissage en pr\u00e9sentiel et en ligne \u00e0 distance.<\/p><p>Les apprenants re\u00e7oivent un dipl\u00f4me certifi\u00e9 par l&rsquo;Universit\u00e9 de la Sorbonne., et 93% des alumnis ont trouv\u00e9 un emploi imm\u00e9diatement. N&rsquo;attendez plus et d\u00e9couvrez <a href=\"https:\/\/datascientest.com\/formation-data-engineer\" target=\"_blank\" rel=\"noopener\">la formation Data Engineer<\/a>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-100e199 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"100e199\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-f2d81e9\" data-id=\"f2d81e9\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-33c3876 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"33c3876\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/formations-data-engineer\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">D\u00e9couvrir la formation Data Engineer<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4be3863 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4be3863\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-eb2c4d8\" data-id=\"eb2c4d8\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-80e4122 elementor-widget elementor-widget-text-editor\" data-id=\"80e4122\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>Vous savez tout sur Apache Pig. D\u00e9couvrez <a href=\"https:\/\/datascientest.com\/hadoop\" target=\"_blank\" rel=\"noopener\">notre dossier complet sur Hadoop<\/a>, et <a href=\"https:\/\/datascientest.com\/sql-tout-savoir\" target=\"_blank\" rel=\"noopener\">notre introduction au langage SQL<\/a>.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-99398c3 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"99398c3\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-91bc43f\" data-id=\"91bc43f\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-410f6aa elementor-widget elementor-widget-html\" data-id=\"410f6aa\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [{\n    \"@type\": \"Question\",\n    \"name\": \"Qu'est-ce que Apache Pig ?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"Le langage de programmation de haut niveau Apache Pig est tr\u00e8s utile pour analyser de larges ensembles de donn\u00e9es. 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Toutefois, les Data Analysts ne ma\u00eetrisent pas toujours ce paradigme. C&rsquo;est [&hellip;]<\/p>\n","protected":false},"author":77,"featured_media":74722,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2497],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Apache Pig : tout savoir sur le langage de programmation d&#039;Hadoop<\/title>\n<meta name=\"description\" content=\"Apache Pig est le langage de programmation du framework de big data Hadoop. D\u00e9couvrez tout ce qu&#039;il y a \u00e0 savoir \u00e0 son sujet.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/datascientest.com\/apache-pig\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Apache Pig : tout savoir sur le langage de programmation d&#039;Hadoop\" \/>\n<meta property=\"og:url\" content=\"https:\/\/datascientest.com\/apache-pig\" \/>\n<meta property=\"og:site_name\" content=\"Formation Data Science | DataScientest.com\" \/>\n<meta property=\"article:published_time\" content=\"2021-06-09T08:16:46+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-11-09T14:07:10+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/datascientest.com\/wp-content\/uploads\/2021\/05\/illu_apachepig_blog.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1024\" \/>\n\t<meta property=\"og:image:height\" content=\"563\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Raphael Kassel\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"Raphael Kassel\" \/>\n\t<meta name=\"twitter:label2\" content=\"Dur\u00e9e de lecture estim\u00e9e\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/datascientest.com\/apache-pig\",\"url\":\"https:\/\/datascientest.com\/apache-pig\",\"name\":\"Apache Pig : tout savoir sur le langage de programmation d'Hadoop\",\"isPartOf\":{\"@id\":\"https:\/\/datascientest.com\/#website\"},\"datePublished\":\"2021-06-09T08:16:46+00:00\",\"dateModified\":\"2023-11-09T14:07:10+00:00\",\"author\":{\"@id\":\"https:\/\/datascientest.com\/#\/schema\/person\/6eca16f63daaafcbc96e15549b9d4ee1\"},\"description\":\"Apache Pig est le langage de programmation du framework de big data Hadoop. 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