In the last year, we've gone from millions of pieces of data to billions of pieces of data. I will speak on a solution for scaling up and about the challenges presented. Also covered will be the future of data at Qihoo 360 with MongoDB.
In the last year, we've gone from millions of pieces of data to billions of pieces of data. I will speak on a solution for scaling up and about the challenges presented. Also covered will be the future of data at Qihoo 360 with MongoDB.
MySQL 5.6 GA版本已经发布了,其中包含了大量的新特性,了解这些新特性,不仅对数据库内核研发有帮助,对于更好的使用MySQL数据库也有着极大的意义。本分享将深入剖析MySQL 5.6新特性的实现细节,一共分为两期:分别是InnoDB引擎以及MySQL Server。本次为第一期,分享 MySQL 5.6 InnoDB引擎中的性能优化与功能增强。
How do we manage more than one thousand of Pegasus clusters - backend partacelyc1112009
A presentation in Apache Pegasus meetup in 2021 from Wang Dan.
Know more about Pegasus https://pegasus.apache.org, https://github.com/apache/incubator-pegasus
Apache Kylin Data Summit 2019: Kyligence PresentationTyler Wishnoff
The 2019 Apache Kylin Data Summit hosted this year in Shanghai provided Big Data analytics experts in IT and on the business side an early look at where this powerful OLAP technology is going. This presentation highlights the work Kyligence is doing to support the Apache Kylin project and deliver a commercial OLAP solution suitable for enterprises working with massive datasets. Founded by the initial creators of Apache Kylin, learn more about Kyligence here: https://kyligence.io/
16. ICP (Index Condition Pushdown)
• 利用索引捞数据时,将可过滤的where条件
传递到SE层,减少回表的次数
• 典型的场景: select * from db.table where and
idx_c1>? and idx_c2<? and non-idx_c3=?
• 其执行的逻辑解释
17. MRR (Multi-Range-Read)
• 顺序读非聚簇索引中结点, 将符合条件的PK
全部捞出来并排序,然后再到聚簇索引中
一次性把记录捞出来处理。
• 典型场景:SELECT * FROM t WHERE
key_part1 >= 1000 AND key_part1 < 2000
AND key_part2 = 10000;
• 其执行的逻辑解释