Introduction of Distributed Key-Value Storage “ okuyama” Kobe Digital Labo, Inc.              http://www.kdl.co.jp/
BigTable Dynamo Tokyo Ty r ant kumofs okuyama What is okuyama? Distributed Key-Value Storage
<ul><li>Distributed KVS, implemented in Java </li></ul><ul><li>Multiple data preservation form </li></ul><ul><li>Performan...
・ 100%Java -Communication Part, Control Part, Data Storage  ・ doesn’t depend on OS -Java Virtual Machine environment ・ Ver...
・ You can choose the way of preservation  to data node Main Data Node 1. Preserve all data to memory - Non-perpetuity type...
・  The scale out is possible without the system hung in both mastering nodes and the data nodes. ・  All the data shifts at...
・ Data Flow Main Master Node Main Data Node Slave Data Node Main Data Node Slave Data Node Main Data Node Slave Data Node ...
5. Function of managing collectively
・  It is not only a relation of Key-Value! >You can add Tags set (Key=“okuyama”, Tag={“oss”, ”kvs”}, Value=“Ditributed KVS...
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  • ・ Java で実装された分散キーバリューストア ・データ保存方式の選択が可能 ・スケールアウトによる性能向上 ・ SPOF の存在しない構成 ・一括管理機能 ・ユニークな機能
  • ・ 100%Java &gt; 通信部分、制御部分、データ保存部分 ・ OS 非依存 &gt;JavaVirtualMachine が動く環境なら動く ・ WindowsXP 系と CentOS5 系で動作検証 &gt; 開発・検証は Windows で負荷テストは CentOS
  • 1. 全てのデータをメモリに保存 &gt; 非永続型 2 . データ操作履歴のみファイルに保存 &gt; 永続型 3. データ本体をファイルに保存 &gt; 永続型
  • Okuyama Summary

    1. 1. Introduction of Distributed Key-Value Storage “ okuyama” Kobe Digital Labo, Inc.              http://www.kdl.co.jp/
    2. 2. BigTable Dynamo Tokyo Ty r ant kumofs okuyama What is okuyama? Distributed Key-Value Storage
    3. 3. <ul><li>Distributed KVS, implemented in Java </li></ul><ul><li>Multiple data preservation form </li></ul><ul><li>Performance gain by scale out </li></ul><ul><li>Composition where SPOF doesn't exist </li></ul><ul><li>Function of managing collectively </li></ul><ul><li>Unique function </li></ul>What is okuyama? -Features
    4. 4. ・ 100%Java -Communication Part, Control Part, Data Storage ・ doesn’t depend on OS -Java Virtual Machine environment ・ Verified on WindowsXP / CentOS5 series -Developed and verified on Windows -Load tested on CentOS <ul><li>Distributed KVS, implemented in Java </li></ul>
    5. 5. ・ You can choose the way of preservation to data node Main Data Node 1. Preserve all data to memory - Non-perpetuity type 2. Only preserve the data operation record to files - Perpetuity type 3. Preserve data themselves to files - Perpetuity type 2. Multiple data preservation form
    6. 6. ・ The scale out is possible without the system hung in both mastering nodes and the data nodes. ・ All the data shifts at the scale out etc. are done by the automatic operation. Main Data Node Slave Data Node Main Data Node Slave Data Node Main Data Node Slave Data Node Main Data Node Slave Data Node Main Data Node Slave Data Node Main Data Node Slave Data Node Add Node Data Shift Add 3. Performance gain by scale out
    7. 7. ・ Data Flow Main Master Node Main Data Node Slave Data Node Main Data Node Slave Data Node Main Data Node Slave Data Node Main Data Node Slave Data Node Client Slave Master Node ① Input Data 4. Composition where SPOF doesn't exist
    8. 8. 5. Function of managing collectively
    9. 9. ・ It is not only a relation of Key-Value! >You can add Tags set (Key=“okuyama”, Tag={“oss”, ”kvs”}, Value=“Ditributed KVS”); set (Key=“httpd”, Tag={“oss”, ”webserver”}, Value=“Typical WebSV”); getTagKeys(“oss”);   >Result {“okuyama”, ”httpd”} You can get all keys, resistered in same tag Data can be grouped! 6.Unique function

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