Dremel made simple with Parquet
Columnar storage is a popular technique to optimize analytical workloads in parallel RDBMs. The performance and compression benefits for storing and processing large amounts of data are well documented in academic literature as well as several commercial analytical databases. The goal is to keep I/O to a minimum by reading from a disk only the data required for the query. Using Parquet at Twitter,
カラムナストレージ - Yet Another HDIF?
Disclaimer: The opinions expressed here are my own and do not necessarily represent those of current or past employers.Twitter / Photos Disclaimer: The opinions expressed here are my own and do not necessarily represent those of current or past employers. Twitter / Photos Henry Robinsonã«ã‚ˆã‚‹ã€ã‚«ãƒ©ãƒ ナストレージã®è§£èª¬è¨˜äº‹ã‚’翻訳ã—ã¾ã—ãŸã€‚カラムナストレージã¯ã€Googleã§é–‹ç™ºã•ã‚ŒãŸãƒ‡ãƒ¼ã‚¿å‡¦ç†ãƒ„ールã§ã‚ã‚‹Dremelã«ä½¿ç”¨ã•ã‚Œã¦ã„るファイルフォーマットã§ã‚ã‚Šã€ClouderaãŒé–‹ç™ºã‚’進ã‚ã‚‹Impalaã§ã‚‚採用
Dremel: Interactive Analysis of Web-Scale Datasets
The document describes Dremel, an interactive analysis system for web-scale datasets. Dremel uses a columnar data storage model and tree-based query serving architecture to enable interactive analysis of trillion record datasets distributed across thousands of nodes. It provides an SQL-like interface and can process queries orders of magnitude faster than traditional MapReduce systems by avoiding
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Google Dremel
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