AWS at Strata+Hadoop 2016: Building a Scalable Architecture on AWS to Process Streaming Data | Amazon Web Services
AWS Big Data Blog AWS at Strata+Hadoop 2016: Building a Scalable Architecture on AWS to Process Streaming Data Gone are the days when big data was confined to batch processing. To remain competitive, companies must be able to analyze real-time data streams in areas such as video streaming, real-time recommendation engines, preventive maintenance, and fraud detection applications. Last month, Siva
Registration: Machine learning & data conference | O'Reilly Strata
We’ve made the very difficult decision to cancel all future O’Reilly in-person conferences. Instead, we’ll continue to invest in and grow O’Reilly online learning, supporting the 5,000 companies and 2.5 million people who count on our experts to help them stay ahead in all facets of business and technology. Come join them and learn what they already know. Become an O’Reilly online learning member
Using logs to build a solid data infrastructure (or: why dual writes are a bad idea) | Confluent
This is an edited transcript of a talk I gave at the Craft Conference 2015. The video and slides are also available. How does your database store data on disk reliably? It uses a log. How does one database replica synchronise with another replica? It uses a log. How does a distributed algorithm like Raft achieve consensus? It uses a log. How does activity data get recorded in a system like Apache
Architectural Patterns for Near Real-Time Data Processing with Apache Hadoop - Cloudera Blog
Architectural Patterns for Near Real-Time Data Processing with Apache Hadoop Evaluating which streaming architectural pattern is the best match to your use case is a precondition for a successful production deployment. The Apache Hadoop ecosystem has become a preferred platform for enterprises seeking to process and understand large-scale data in real time. Technologies like Apache Kafka, Apache F
In-Stream Big Data Processing
The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. In recent years, this idea got a lot of traction and a whole bunch of solutions like Twitter’s Storm, Yahoo’s S4, Cloudera’s Impala, Apa
1
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
http://www.vldb.org/pvldb/vol7/p1441-boykin.pdf
Photon: Fault-tolerant and Scalable Joining of Continuous Data Streams
