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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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Top Key Architecture Components in HIVE

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5 architectural components present in Hadoop Hive: Shell: allows interactive queries like MySQL shell connected to a database – Also supports web and JDBC clients Driver: session handles, fetch, execute Compiler: parse, plan, optimize Execution engine: DAG of stages (M/R, HDFS, or metadata) Metastore: schema, location in HDFS, SerDe

 Data Mode of Hive:
  • Tables
– Typed columns (int, float, string, date, boolean)
– Also, list: map (for JSON-like data)
  • Partitions
– e.g., to range-partition tables by date
  • Buckets
– Hash partitions within ranges (useful for sampling, join optimization)

HIVE Meta Store
  • Database: namespace containing a set of tables
  • Holds table definitions (column types, physical layout)
  • Partition data 
  • Uses JPOX ORM for implementation; can be stored in Derby, MySQL, many other relational databases
Physical Layout of HIVE
  • Warehouse directory in HDFS
– e.g., /home/hive/warehouse
  • Tables stored in subdirectories of warehouse
– Partitions, buckets form subdirectories of tables
  • Actual data stored in flat files
– Control char-delimited text, or SequenceFiles
– With custom SerDe, can use arbitrary format

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