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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...
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How to verify SSH Installed in Hadoop Cluster Quickly

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Below command helps, whether SSH is installed or not on your Hadoop cluster.

[hadoop-user@master]$ which ssh
/user/bin/bash
[hadoop-user@master] $ which sshd
/user/bin/sshd
[hadoop-user@master] $ which ssh -keygen
/user/bin/sshd

 If you do not get proper response as above. That means that SSH is not installed on your cluster.

Resolution:

If you receive an error message

/user/bin/which: no ssh in (/user/bin: /user/sbin....)

You need to install open SSH (www.openssh.com) vial Linux package manager. Or by downloading the source directly.

Note: This is usually done by System Admin.

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