The document discusses best practices for operating and supporting Apache HBase. It outlines tools like the HBase UI and HBCK that can be used to debug issues. The top categories of issues covered are region server stability problems, read/write performance, and inconsistencies. SmartSense is introduced as a tool that can help detect configuration issues proactively.
The document discusses best practices for operating and supporting Apache HBase. It outlines tools like the HBase UI and HBCK that can be used to debug issues. The top categories of issues covered are region server stability problems, read/write performance, and inconsistencies. SmartSense is introduced as a tool that can help detect configuration issues proactively.
This slides explains why Paxos is the only correctly way to problems about consensus in a distributed system.
This slides uses several diagram to show how paxos is derived from a naive replication algorithm to a immediate consistent replication algorithm.
It starts with master-slave replication.
Then we refine it to quorum-rw by adding consistency constrain.
And then we refine quorum-rw to paxos by adding atomicity constrain.
Aggregated queries with Druid on terrabytes and petabytes of dataRostislav Pashuto
The document discusses Druid, an open-source distributed column-oriented data store designed for low latency queries on large datasets. It outlines Druid's capabilities for real-time ingestion, aggregation queries in sub-seconds, and storing petabytes of historical data. Examples are given of companies like Netflix and PayPal using Druid at large scales to analyze streaming data. The key components, data formats, and query types of Druid are described.
投影片講解視訊影片網址:
http://www.youtube.com/playlist?list=PLFL0ylDooClTXfy-cFbq7rV1iwP57JFaF
This slide is made by the RoBoard team of DMP Electronics Inc.:
https://www.facebook.com/roboard.fans
[資料科學實用技術、工具與實例分享]
資料科學涵蓋工程、分析、領域三種不同面向,為了能夠由資料中發現真實價值,需要各式各樣輔助我們達成目標的技術或是工具,如資料處理、資料分析與視覺化等等。
本次演講將由Shaw Wu來為各位簡單分享各種可用工具或套件,並搭配個人生活中一些無聊的資料科學應用嘗試,提供大家踏入資料科學領域時的一些參考。
#Beehive Data Group
Honey's Data Dinner#1 word2vec 2016總統大選新聞beehivedata
【word2vec 2016總統大選新聞】
講者:施旭峰
主辦單位:蜂巢數據(Beehive Data Group)
word2vec 是 Google 2013 年年中釋出基於 Apache 2.0 的開源專案,常被歸類在 Deep Learning 的一環。這次的晚餐時間,我們會分享利用 2016總統大選收集的新聞資料實作 word2vec 的過程,歡迎一起來晚餐唷!
#Beehive Data Group
Arduino is a popular hardware platform for IoT projects. This document discusses connecting Arduino devices to the web and cloud services. It introduces IoT concepts and components like hardware devices, communication protocols, data storage, and business logic. Ways to connect Arduino to web servers using libraries and shields are described. Popular cloud IoT platforms like ThingSpeak and Temboo and how to use them with Arduino Yun are also covered.
This document summarizes the roles of servers in a Hadoop cluster, including manager, name nodes, edge nodes, and data nodes. It discusses hardware considerations for Hadoop cluster design like CPU to memory to disk ratios for different use cases. It also provides an overview of Dell's Hadoop solutions that integrate PowerEdge servers, Dell Networking switches, and support from Etu for analytic software and Dell Professional Services for implementation. It briefly discusses futures around in-memory processing and virtualized Hadoop deployments.
This slides explains why Paxos is the only correctly way to problems about consensus in a distributed system.
This slides uses several diagram to show how paxos is derived from a naive replication algorithm to a immediate consistent replication algorithm.
It starts with master-slave replication.
Then we refine it to quorum-rw by adding consistency constrain.
And then we refine quorum-rw to paxos by adding atomicity constrain.
Aggregated queries with Druid on terrabytes and petabytes of dataRostislav Pashuto
The document discusses Druid, an open-source distributed column-oriented data store designed for low latency queries on large datasets. It outlines Druid's capabilities for real-time ingestion, aggregation queries in sub-seconds, and storing petabytes of historical data. Examples are given of companies like Netflix and PayPal using Druid at large scales to analyze streaming data. The key components, data formats, and query types of Druid are described.
投影片講解視訊影片網址:
http://www.youtube.com/playlist?list=PLFL0ylDooClTXfy-cFbq7rV1iwP57JFaF
This slide is made by the RoBoard team of DMP Electronics Inc.:
https://www.facebook.com/roboard.fans
[資料科學實用技術、工具與實例分享]
資料科學涵蓋工程、分析、領域三種不同面向,為了能夠由資料中發現真實價值,需要各式各樣輔助我們達成目標的技術或是工具,如資料處理、資料分析與視覺化等等。
本次演講將由Shaw Wu來為各位簡單分享各種可用工具或套件,並搭配個人生活中一些無聊的資料科學應用嘗試,提供大家踏入資料科學領域時的一些參考。
#Beehive Data Group
Honey's Data Dinner#1 word2vec 2016總統大選新聞beehivedata
【word2vec 2016總統大選新聞】
講者:施旭峰
主辦單位:蜂巢數據(Beehive Data Group)
word2vec 是 Google 2013 年年中釋出基於 Apache 2.0 的開源專案,常被歸類在 Deep Learning 的一環。這次的晚餐時間,我們會分享利用 2016總統大選收集的新聞資料實作 word2vec 的過程,歡迎一起來晚餐唷!
#Beehive Data Group
Arduino is a popular hardware platform for IoT projects. This document discusses connecting Arduino devices to the web and cloud services. It introduces IoT concepts and components like hardware devices, communication protocols, data storage, and business logic. Ways to connect Arduino to web servers using libraries and shields are described. Popular cloud IoT platforms like ThingSpeak and Temboo and how to use them with Arduino Yun are also covered.
This document summarizes the roles of servers in a Hadoop cluster, including manager, name nodes, edge nodes, and data nodes. It discusses hardware considerations for Hadoop cluster design like CPU to memory to disk ratios for different use cases. It also provides an overview of Dell's Hadoop solutions that integrate PowerEdge servers, Dell Networking switches, and support from Etu for analytic software and Dell Professional Services for implementation. It briefly discusses futures around in-memory processing and virtualized Hadoop deployments.