How manuurc12-hash/examen-segundo-parcial---manejo-de-datos works
This repository processes sales data into category-and-month revenue totals, with a sequential implementation and separate Hadoop-style mapper/reducer scripts. Loader scripts import processed output into PostgreSQL, which a FastAPI service exposes through read and write endpoints. The source excerpts do not show a job orchestrator wiring the mapper to the reducer, so that connection is omitted; the README is empty.
Main entry points: mapper.py Revenue mapper · reducer.py Revenue reducer · cargar_resultados.py File results loader · cargar_directo.py Direct file loader
Components 12
Revenue aggregation
- Revenue mapper
app/mapper.py - Revenue reducer
app/reducer.py - Sequential aggregator
app/secuencial.py
Result loading
- File results loader
app/cargar_resultados.py - Direct file loader
app/cargar_directo.py - Hadoop loader
app/cargar_definitivo.py - PostgreSQL results
Results API
- Results API
app/main.py
Other components
- Data operator
- CSV input stream
- MapReduce output file
- Hadoop output
Connections 12
- Data operator → Results API: requests
app/main.py - Results API → PostgreSQL results: reads and writes
app/main.py - CSV input stream → Revenue mapper: reads stream
app/mapper.py - Revenue mapper → Revenue reducer: emits records
- Revenue reducer → MapReduce output file: emits totals
- CSV input stream → Sequential aggregator: reads CSV
app/secuencial.py - MapReduce output file → File results loader: reads records
app/cargar_resultados.py - MapReduce output file → Direct file loader: reads records
app/cargar_directo.py - Hadoop output → Hadoop loader: reads output
app/cargar_definitivo.py - File results loader → PostgreSQL results: inserts rows
app/cargar_resultados.py - Direct file loader → PostgreSQL results: inserts rows
app/cargar_directo.py - Hadoop loader → PostgreSQL results: inserts rows
app/cargar_definitivo.py