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SQL on Big Data

Technology, Architecture, and Innovation

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Discover various commercial and open-source products that execute SQL on Big Data platforms, gaining insights into the architectures of SQL engines and their internal workings regarding execution, data movement, latency, scalability, performance, and system requirements. This resource consolidates solutions to challenges related to speed, scalability, and diverse operations required for data integration and SQL tasks. It begins with a historical overview of SQL on Big Data, then delves into the products, architectures, and innovations in this rapidly evolving field. The discussion includes the advancements in performance, scalability, and the ability to manage different data types. The text covers SQL on Big Data engines' impact on OLTP, OLAP, operational analytics, and emerging HTAP systems. Key topics include: **Batch Architectures**—the evolution of the Hive engine for improved query latency; **Interactive Architectures**—designs that support low latency for large datasets; **Streaming Architectures**—architectures enabling queries on real-time data using in-memory structures; **Operational Architectures**—supporting transactions on Big Data platforms; and **Innovative Architectures**—exploring new SQL engines with groundbreaking concepts. This resource is ideal for business analysts, BI engineers, developers, data scientists, architects, and quality assurance professionals.

Acquisto del libro

SQL on Big Data, Sumit Pal

Lingua
Pubblicato
2016
Rilegatura
(In brossura)
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Metodi di pagamento

Titolo
SQL on Big Data
Sottotitolo
Technology, Architecture, and Innovation
Lingua
Inglese
Autori
Sumit Pal
Editore
Apress
Pubblicato
2016
Formato
In brossura
Pagine
157
ISBN10
1484222466
ISBN13
9781484222461
Serie
Descrizione
Discover various commercial and open-source products that execute SQL on Big Data platforms, gaining insights into the architectures of SQL engines and their internal workings regarding execution, data movement, latency, scalability, performance, and system requirements. This resource consolidates solutions to challenges related to speed, scalability, and diverse operations required for data integration and SQL tasks. It begins with a historical overview of SQL on Big Data, then delves into the products, architectures, and innovations in this rapidly evolving field. The discussion includes the advancements in performance, scalability, and the ability to manage different data types. The text covers SQL on Big Data engines' impact on OLTP, OLAP, operational analytics, and emerging HTAP systems. Key topics include: **Batch Architectures**—the evolution of the Hive engine for improved query latency; **Interactive Architectures**—designs that support low latency for large datasets; **Streaming Architectures**—architectures enabling queries on real-time data using in-memory structures; **Operational Architectures**—supporting transactions on Big Data platforms; and **Innovative Architectures**—exploring new SQL engines with groundbreaking concepts. This resource is ideal for business analysts, BI engineers, developers, data scientists, architects, and quality assurance professionals.