spark
Apache Spark
DAG scheduler, stage boundaries, shuffle internals, RDD vs DataFrame, and memory management in Spark 3.x.
hadoop
Hadoop
HDFS architecture, MapReduce internals, YARN resource management, and the Hadoop ecosystem overview.
hive
Hive
HiveQL, partitioning strategies, bucketing, metastore architecture, and query optimization techniques.
pyspark
PySpark
DataFrame API, transformations vs actions, UDFs, Spark SQL integration, and performance tuning patterns.
python
Python
Data engineering patterns — generators, decorators, async I/O, type hints, and testing with pytest.
sql
SQL
Window functions, CTEs, execution plans, indexing strategies, and advanced aggregation patterns.