The Cassandra File System (CFS) is an HDFS compatible filesystem built to replace the traditional Hadoop NameNode, Secondary NameNode and DataNode daemons. It is the foundation of our Hadoop support in DataStax Enterprise. The main design goals for the Cassandra File System were to first, simplify the operational overhead of Hadoop by removing the single points of failure in the Hadoop NameNode. S
Introduction to Compaction Cassandra's log-structured storage engine enables Cassandra's amazing performance and features like application-transparent compression by turning all updates into data files called sstables that are written sequentially to disk. No update-in-place is done (because that would require doing random i/o); instead, a new version of the columns being inserted or updated is wr
As we've worked towards 1.0 over the past year, Cassandra's performance has improved spectacularly. Compared to the current release this time in 2010, we've increased our write performance a respectable 40%. But the real area we wanted to focus on improving was read performance, which we succeeded in increasing a phenomenal 400%! Reads There are actually two different execution paths for reads in
Slides and Videos from Cassandra NYC 2011 will be posted here. Thanks to all that attended and we look forward to seeing you next year! Chris Burroughs (Clearspring) – Apache Cassandra at Clearspring (HD Video) David Weinstein (Adobe) – Cassandra at Adobe (HD Video) Drew Robb (SocialFlow) – Cassandra at Social Flow (HD Video) Ed Capriolo (m6d) – Cassandra in Online Advertising (Slides and HD Video
Twitter currently runs a couple hundred Cassandra nodes across a half dozen clusters. These span a variety of workloads– from time series to data, to low latency, high throughput key/value. Each workload has led the team to new techniques for operating Cassandra at scale. Chris Goffinet, an engineer at Twitter and Cassandra committer, will be sharing some of the most interesting ones. For those of
By Andrew Llavore - July 18, 2011 Jonathan Ellis, CTO of DataStax and project chair for Apache Cassandra, keynoted at Cassandra SF 2011. Major accomplishments for the project in the last year include better support for multi-data center deployments, optimized read performance, included integrated caching and improved client APIs including a SQL-like language CQL. Read More
Spotlight InfoWorld Technology of the Year DataStax Enterprise has been named a 2019 InfoWorld Technology of the Year Read Now Overview In Cassandra 0.6, we created a ColumnFamilyInputFormat, allowing you to read data stored in Cassandra from a Hadoop mapreduce job. However, you had to write the output from these jobs to a local file or HDFS, or manually connect to Cassandra in your reducer to sto
NOTE: This post pre-dates our Brisk announcement. Brisk is a new distribution that enhances the Hadoop and Hive platform with scalable low-latency data capabilities. In our December post, we introduced the class ColumnFamilyInputFormat and fleshed it out in the context of a detailed MapReduce example. If you are interested in running MapReduce with Cassandra and haven’t read that post yet, it is h
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
処理を実行中です
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く