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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...

Oozie - Concepts And Architecture

Oozie is a workflow/coordination system that you can use to manage Apache Hadoop jobs. It is one of the main components of Oozie is the Oozie server — a web application that runs in a Java servlet container (the standard Oozie distribution is using Tomcat).

Oozie is a workflow management-server that works on the Oozie server.

Role of Oozie in Workflow Management in Hadoop Jobs

  1. This server supports reading and executing Workflows, Coordinators, Bundles, and SLA definitions. It implements a set of remote Web Services APIs that can be invoked from Oozie client components and third-party applications.
  2. Add a note where the execution of the server leverages a customizable database.
  3. This database contains Workflow, Coordinator, Bundle, and SLA definitions, as well as execution states and process variables.
  4. The list of currently supported databases includes MySQL, Oracle, and Apache Derby. The Oozie shared library component is located in the Oozie HOME directory and contains code used by the Oozie execution.

Oozie Architecture

oozie architecture


How to work with Oozie in Hadoop Framework

Oozie provides a command-line interface (CLI) that is based on a client component, which is a thin Java wrapper around Oozie Web Services APIs.

These APIs can also be used from third-party applications that have sufficient permissions.
A single Oozie server implements all four functional Oozie components:
  • Oozie Workflow 
  • Oozie Coordinator 
  • Oozie Bundle 
  • Oozie SLA 
  • Oozie server is described in this chapter, starting with what Oozie Workflow is and how you can use it.

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