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Spatial SQL for Data Engineers: Mastering PostGIS, pgRouting, and Spatial Indexing: Writing High-Performance Geospatial Queries, Building Routing Networks, and Scaling PostGIS Databases - Softcover
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Unlock the Full Power of Spatial Data Engineering with PostGIS and PostgreSQL.
Are you a data engineer or backend developer struggling with slow spatial queries, complex coordinate transformations, or massive geospatial datasets that crash traditional database indexes? Geospatial data is no longer a niche requirement reserved for GIS analysts—it is a core component of modern data engineering, logistics, and telemetry systems.
In Spatial SQL for Data Engineers, Dr. Si Mokrane SIAD bridges the gap between traditional relational database management and advanced spatial mathematics. Drawing from his background as a Senior Scientist in Computational Modelling, Dr. Siad breaks down exactly how to architect, index, and query spatial data natively within PostgreSQL without relying on slow application-layer processing.
Here is what you will learn in this playbook:
- Spatial Foundations & CRSs: Master the difference between Geometry and Geography types, and perform precise coordinate transformations (SRID) to avoid silent spatial errors in production.
- Advanced Vector Operations: Write complex spatial joins, nearest neighbor (KNN) searches, and intersections natively in SQL.
- High-Performance Indexing: Implement and tune GiST indexes and R-Trees to drop spatial query times from minutes to milliseconds, leveraging bounding-box logic for massive telemetry tables.
- Network Routing: Build dynamic graph topologies and calculate the shortest paths using Dijkstra's Algorithm and A* Search directly inside the database with pgRouting.
- Discrete Global Grids & H3: Aggregate billions of raw GPS points into Uber's H3 hexagonal grid system and Geohashes for rapid density mapping and reporting.
- ETL & Scaling: Integrate PostGIS with Python, GDAL/ogr2ogr, and Airflow. Architect your databases for scale using spatial table partitioning and connection pooling for cloud deployments (AWS RDS/Aurora).
Whether you are building a fleet tracking API, performing urban network analysis, or simply migrating shapefiles into a robust data warehouse, this book provides the exact SQL, architectural theory, and engineering context you need.
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Spatial SQL for Data Engineers (Paperback)
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Paperback. Zustand: new. Paperback. Unlock the Full Power of Spatial Data Engineering with PostGIS and PostgreSQL.Are you a data engineer or backend developer struggling with slow spatial queries, complex coordinate transformations, or massive geospatial datasets that crash traditional database indexes? Geospatial data is no longer a niche requirement reserved for GIS analysts-it is a core component of modern data engineering, logistics, and telemetry systems.In Spatial SQL for Data Engineers, Dr. Si Mokrane SIAD bridges the gap between traditional relational database management and advanced spatial mathematics. Drawing from his background as a Senior Scientist in Computational Modelling, Dr. Siad breaks down exactly how to architect, index, and query spatial data natively within PostgreSQL without relying on slow application-layer processing.Here is what you will learn in this playbook: Spatial Foundations & CRSs: Master the difference between Geometry and Geography types, and perform precise coordinate transformations (SRID) to avoid silent spatial errors in production.Advanced Vector Operations: Write complex spatial joins, nearest neighbor (KNN) searches, and intersections natively in SQL.High-Performance Indexing: Implement and tune GiST indexes and R-Trees to drop spatial query times from minutes to milliseconds, leveraging bounding-box logic for massive telemetry tables.Network Routing: Build dynamic graph topologies and calculate the shortest paths using Dijkstra's Algorithm and A* Search directly inside the database with pgRouting.Discrete Global Grids & H3: Aggregate billions of raw GPS points into Uber's H3 hexagonal grid system and Geohashes for rapid density mapping and reporting.ETL & Scaling: Integrate PostGIS with Python, GDAL/ogr2ogr, and Airflow. Architect your databases for scale using spatial table partitioning and connection pooling for cloud deployments (AWS RDS/Aurora).Whether you are building a fleet tracking API, performing urban network analysis, or simply migrating shapefiles into a robust data warehouse, this book provides the exact SQL, architectural theory, and engineering context you need. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9798186724971
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Spatial SQL for Data Engineers: Mastering PostGIS, pgRouting, and Spatial Indexing: Writing High-Performance Geospatial Queries, Building Routing Networks, and Scaling PostGIS Databases
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Spatial SQL for Data Engineers : Mastering PostGIS, pgRouting, and Spatial Indexing: Writing High-Performance Geospatial Queries, Building Routing Networks, and Scaling PostGIS Databases
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Taschenbuch. Zustand: Neu. Neuware - Unlock the Full Power of Spatial Data Engineering with PostGIS and PostgreSQL.Are you a data engineer or backend developer struggling with slow spatial queries, complex coordinate transformations, or massive geospatial datasets that crash traditional database indexes Geospatial data is no longer a niche requirement reserved for GIS analysts-it is a core component of modern data engineering, logistics, and telemetry systems.In Spatial SQL for Data Engineers, Dr. Si Mokrane SIAD bridges the gap between traditional relational database management and advanced spatial mathematics. Drawing from his background as a Senior Scientist in Computational Modelling, Dr. Siad breaks down exactly how to architect, index, and query spatial data natively within PostgreSQL without relying on slow application-layer processing.Here is what you will learn in this playbook: - Spatial Foundations & CRSs: Master the difference between Geometry and Geography types, and perform precise coordinate transformations (SRID) to avoid silent spatial errors in production.- Advanced Vector Operations: Write complex spatial joins, nearest neighbor (KNN) searches, and intersections natively in SQL.- High-Performance Indexing: Implement and tune GiST indexes and R-Trees to drop spatial query times from minutes to milliseconds, leveraging bounding-box logic for massive telemetry tables.- Network Routing: Build dynamic graph topologies and calculate the shortest paths using Dijkstra's Algorithm and A\* Search directly inside the database with pgRouting.- Discrete Global Grids & H3: Aggregate billions of raw GPS points into Uber's H3 hexagonal grid system and Geohashes for rapid density mapping and reporting.- ETL & Scaling: Integrate PostGIS with Python, GDAL/ogr2ogr, and Airflow. Architect your databases for scale using spatial table partitioning and connection pooling for cloud deployments (AWS RDS/Aurora).Whether you are building a fleet tracking API, performing urban network analysis, or simply migrating shapefiles into a robust data warehouse, this book provides the exact SQL, architectural theory, and engineering context you need. Bestandsnummer des Verkäufers 9798186724971
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Paperback. Zustand: new. Paperback. Unlock the Full Power of Spatial Data Engineering with PostGIS and PostgreSQL.Are you a data engineer or backend developer struggling with slow spatial queries, complex coordinate transformations, or massive geospatial datasets that crash traditional database indexes? Geospatial data is no longer a niche requirement reserved for GIS analysts-it is a core component of modern data engineering, logistics, and telemetry systems.In Spatial SQL for Data Engineers, Dr. Si Mokrane SIAD bridges the gap between traditional relational database management and advanced spatial mathematics. Drawing from his background as a Senior Scientist in Computational Modelling, Dr. Siad breaks down exactly how to architect, index, and query spatial data natively within PostgreSQL without relying on slow application-layer processing.Here is what you will learn in this playbook: Spatial Foundations & CRSs: Master the difference between Geometry and Geography types, and perform precise coordinate transformations (SRID) to avoid silent spatial errors in production.Advanced Vector Operations: Write complex spatial joins, nearest neighbor (KNN) searches, and intersections natively in SQL.High-Performance Indexing: Implement and tune GiST indexes and R-Trees to drop spatial query times from minutes to milliseconds, leveraging bounding-box logic for massive telemetry tables.Network Routing: Build dynamic graph topologies and calculate the shortest paths using Dijkstra's Algorithm and A* Search directly inside the database with pgRouting.Discrete Global Grids & H3: Aggregate billions of raw GPS points into Uber's H3 hexagonal grid system and Geohashes for rapid density mapping and reporting.ETL & Scaling: Integrate PostGIS with Python, GDAL/ogr2ogr, and Airflow. Architect your databases for scale using spatial table partitioning and connection pooling for cloud deployments (AWS RDS/Aurora).Whether you are building a fleet tracking API, performing urban network analysis, or simply migrating shapefiles into a robust data warehouse, this book provides the exact SQL, architectural theory, and engineering context you need. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798186724971
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