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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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Hadoop: How to find which file is healthy

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Hadoop provides file system health check utility which is called "fsck". Basically, it checks the health of all the files under a path It also checks the health of all the files under the '/'(root). BIN/HADOOP fsck / - It checks the health of all the files BIN/HADOOP fsck /test/ - It checks the health of files under the path By default fsck utility cannot do anything for under replicated blocks and over replicated blocks. Hadoop itself heal the blocks.   How to find which file is healthy It prints out dot for each healthy file It will print a message for each file, if it is not healthy, also for under replicated blocks, over replicated blocks, mis-replicated blocks, and corrupted blocks. By default fsck utility cannot do anything for under replicated blocks and over replicated blocks. Hadoop itself heal the blocks. How to delete corrupted blocks BIN/HADOOP fsck -delete block-names It will delete all corrupted blocks BIN/HADOOP fsck -m...
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