TY - ENCYC
T1 - Wildfire: HTAP for Big Data
AU - Barber, Ronald
AU - Raman, Vijayshankar
AU - Sidle, Richard
AU - Tian, Yuanyuan
AU - Tözün, Pinar
N1 - Note til JCG: ingen BFI-points for denne publikationstype. /PFOR 13-12-2019
JCG: husk at slette denne note.
PY - 2019
Y1 - 2019
N2 - Emerging large-scale real-time analytic applications (real-time inventory/pricing /recommendations, fraud detection, risk analysis, IoT, etc.) require data management systems that can handle fast transactions (OLTP) and analytics (OLAP) simultaneously. Some of them even require analytical queries as part of a transaction. Efficient processing of transactional and analytical requests, however, leads to different design decisions in a system. This article presents the Wildfire system, which targets hybrid transactional and analytical processing (HTAP) for big data. Wildfire leverages Apache Spark to enable large-scale data processing with different types of complex analytical requests and columnar data processing to enable fast transactions and analytics concurrently.
AB - Emerging large-scale real-time analytic applications (real-time inventory/pricing /recommendations, fraud detection, risk analysis, IoT, etc.) require data management systems that can handle fast transactions (OLTP) and analytics (OLAP) simultaneously. Some of them even require analytical queries as part of a transaction. Efficient processing of transactional and analytical requests, however, leads to different design decisions in a system. This article presents the Wildfire system, which targets hybrid transactional and analytical processing (HTAP) for big data. Wildfire leverages Apache Spark to enable large-scale data processing with different types of complex analytical requests and columnar data processing to enable fast transactions and analytics concurrently.
U2 - 10.1007/978-3-319-63962-8257-1
DO - 10.1007/978-3-319-63962-8257-1
M3 - Encyclopedia chapter
BT - Encyclopedia of Big Data Technologies
PB - Springer
ER -