REST API ΰΆැΰΆ± ΰΆΰΆෙΰΆ± ΰΆΰΆ±්ΰΆ± ΰΆ΄ΰΆ§ΰΆ±් ΰΆΰΆ±්ΰΆ±ΰΆොΰΆ§ ΰΆ±ිΰΆΰΆ»ΰΆΈ ΰΆ
ΰ·ΰΆ±්ΰΆ±ΰΆ§ ΰΆ½ැΰΆΆෙΰΆ± ΰ·ΰΆ ΰΆ±ΰΆΊΰΆ් ΰΆΰΆΈΰΆΊි stateless ΰΆිΰΆΊΰΆ± ΰΆΰΆ. π ΰΆΰ·ෙΰΆ±්ΰΆ±ේ ΰ·ΰΆ»ΰΆ½ΰΆΊි ΰ·ΰΆේ, ΰΆ±ΰΆΈුΰΆ් ΰΆΰΆ්ΰΆΰΆ§ΰΆΈ ΰΆΈේΰΆ ΰΆΰΆΈΰΆΊි ΰΆ±ΰ·ීΰΆ± ΰ·ෙΰΆΆ් ΰΆාΰΆ්ΰ·ΰΆ«ΰΆΊේ ΰΆ΄ΰΆ―ΰΆ±ΰΆΈ් ΰ·ූ ΰ·ැΰΆ―ΰΆΰΆ්ΰΆΈ architectural ΰΆීΰΆ»ΰΆ«ΰΆΊΰΆ්. ΰΆΰΆිΰΆ±් ΰ·ΰΆ»ΰΆ½ΰ·ΰΆΈ ΰΆΈේΰΆ ΰΆේΰΆ»ුΰΆΈ් ΰΆΰΆΈු. π π€ "Stateless" ΰΆිΰΆΊΰΆ±්ΰΆ±ේ ΰΆΰΆ්ΰΆΰΆ§ΰΆΈ ΰΆΈොΰΆΰΆ්ΰΆ―? Stateless ΰΆ΄ΰΆ―්ΰΆ°ΰΆිΰΆΊΰΆ ΰ·ΰΆ»්ΰ·ΰΆ»් π₯️ ΰΆΰΆ client ΰΆේ ΰΆ΄ෙΰΆ» requests ΰΆැΰΆ± ΰΆිΰ·ිΰΆΈ ΰΆ―ෙΰΆΊΰΆ් ΰΆΈΰΆΰΆ ΰΆිΰΆΊාΰΆΰΆ±්ΰΆ±ේ ΰΆ±ැΰ·ැ . Client ΰΆෙΰΆ±ෙΰΆුΰΆෙΰΆ±් server ΰΆΰΆΰΆ§ ΰΆΰΆ± ΰ·ැΰΆΈ request ΰΆΰΆΰΆΰΆΈ, ΰΆ request ΰΆΰΆ ΰΆේΰΆ»ුΰΆΈ් ΰΆΰΆ±්ΰΆ±ΰΆ් process ΰΆΰΆ»ΰΆ±්ΰΆ±ΰΆ් ΰΆ
ΰ·ΰ·්ΰΆΊ ΰ·ΰΆΈ්ΰΆ΄ූΰΆ»්ΰΆ« ΰΆොΰΆ»ΰΆුΰΆ»ු π¦ ΰΆිΰΆΆෙΰΆ±්ΰΆ±ΰΆΈ ΰΆΰΆ± — server ΰΆΰΆΰΆ§ "ΰΆΰΆ½ිΰΆ±් ΰΆΈΰΆΰΆ ΰΆිΰΆΊෙΰΆ±" ΰΆිΰ·ිΰΆΈ ΰΆ―ෙΰΆΊΰΆ් ΰΆ±ැΰ·ැ. ΰΆΈේΰΆ fast-food ΰΆΰ·ුΰΆ±්ΰΆ§ΰΆ»ΰΆΊΰΆ ΰΆΰ·ාΰΆ» order ΰΆΰΆ»ΰΆ±ΰ·ා ΰ·ΰΆේ ΰΆ―ෙΰΆΊΰΆ්. π ΰ·ැΰΆΈ ΰ·ΰΆාΰ·ෙΰΆΈ ΰΆΰΆΆ ΰΆිΰ·ිΰΆ±් ΰΆΰΆΆේ ΰ·ΰΆΈ්ΰΆ΄ූΰΆ»්ΰΆ« order ΰΆΰΆ ΰΆ±ැΰ·ΰΆ ΰΆිΰΆΊΰΆ±්ΰΆ± ΰΆΰΆ± — "ΰΆΆΰΆ»්ΰΆΰΆ»් ΰΆΰΆΰΆ්, ΰ·
ූΰΆ«ු ΰΆ±ෑ, ΰΆ ීΰ·් ΰ·ැΰΆ©ිΰΆΊ, ΰΆΈΰΆ°්ΰΆΊΰΆΈ ΰΆ΄්ΰΆ»ΰΆΈාΰΆ«ΰΆΊේ ΰ·්ΰΆ»ΰΆΊිΰ·්, ΰΆෝΰΆ½ා ΰΆΰΆΰΆ්" ΰΆිΰΆΊΰΆ½ා ππ₯€. ΰΆැΰ·ිΰΆΊΰΆ»්ΰΆ§ ΰΆΈΰΆΰΆ ΰΆ±ැΰ·ැ ΰΆΰΆΆ ΰΆ΄ΰ·ුΰΆිΰΆΊ ΰ·ΰΆිΰΆΊේ order ΰΆΰ·
ේ ΰΆΈොΰΆΰΆ්ΰΆ―, ΰΆΈිΰΆ±ිΰΆ්ΰΆු ΰΆ΄ΰ·ΰΆΰΆ§ ΰΆΰΆ½ිΰΆ±් ΰ·ුΰΆ±ΰΆ් ΰ·ΰΆ»ි. ΰ·ැΰΆΈ order ΰΆΰΆΰΆ්ΰΆΈ ΰΆΰΆිΰΆ±ෙΰΆΰΆ§ ΰ·ෙΰΆ±් ΰ·ෙΰΆ½ා ΰΆිΰΆΊෙΰΆ±ΰ·ා. ✅ π️ REST APIs ΰ·ΰΆ½ ΰΆΈේΰΆ ΰ·ැΰΆ© ΰΆΰΆ»ΰΆ±්ΰΆ±ේ ΰΆොΰ·ොΰΆΈΰΆ―? Stateless REST API ΰΆΰΆΰΆ: π Client ΰΆΰΆ authentication ...
In the era of big data, organizations are constantly seeking efficient ways to manage, process, and analyze large volumes of structured and unstructured data. Enter Apache Hadoop , an open-source framework that provides scalable, reliable, and distributed computing solutions. With its rich ecosystem of tools, Hadoop has become a cornerstone for big data projects. Let’s explore the various components and layers of the Hadoop ecosystem and how they work together to deliver insights. Data Processing Layer π ️π The heart of Hadoop lies in its data processing capabilities, powered by several essential tools: Apache Pig π· : Allows Hadoop users to write complex MapReduce transformations using a scripting language called Pig Latin , which translates to MapReduce and executes efficiently on large datasets. Apache Hive π : Provides a SQL-like query language called HiveQL for summarizing, querying, and analyzing data stored in Hadoop’s HDFS or compatible systems like Amazon S3. It makes inter...