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研究生： 楊國佑
Yang, Guo-You
論文名稱： 基於Apache Phoenix的JSON資料型態實作
Supporting JSON Data Type in Apache Phoenix
指導教授： 蕭宏章
Hsiao, Hung-Chang
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年： 2015
畢業學年度： 103
語文別： 英文
論文頁數： 30
中文關鍵詞： HBase 、Phoenix 、JSON
外文關鍵詞： HBase, Phoenix, JSON
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    • 隨著4G網路的普及，物聯網（Internet of Things）也變得更加熱門。在越來越多裝置能上網的情況下，訊息的傳遞會變得更加頻繁，而在這些訊息背後隱藏的是以往不曾出現的各種數據。在眾多裝置的訊息傳遞格式中，以JSON的傳遞格式最為流行，由於JSON格式容易理解，JavaScript 的普遍性，傳輸快速且佔空間小的特性使其逐漸成為主流，因此一個能收集巨量JSON資料的資料庫及DBMS會是未來所需要的。為了達成此目標我們使用HBase當成資料庫同時修改Apache Phoenix使其支援JSON格式，提供使用者使用SQL命令就能存取JSON資料。

    With the popularity of 4G network, IOT (Internet of Things) becomes more and more popular. With more devices can access Internet, transfer of message will become more frequently, and hiding in the background is a variety of data previously not appear. In many kinds of transfer format, JSON format is the most popular format. Since JSON format is easy to understand, universality of JavaScript, occupy less transmission characteristics space make it become mainstream. Therefore a database that is able to collect a huge amount of JSON data and a DBMS will be need in the future. To achieve this goal we use HBase as database and modify Apache Phoenix to support JSON format, provide user an easy way to access JSON by using SQL commands.

    摘要 i ABSTRACT ii ACKNOWLEDGEMENTS iii TABLE OF CONTENTS iv LIST OF TABLES vi LIST OF FIGURES vii CHAPTER 1 INTRODUCTION 1 CHAPTER 2 RELATED WORK 3 2.1 Apache Hadoop 3 2.2 Apache HBase 4 2.3 HBase Coprocessor 7 2.4 Apache Phoenix 8 2.4.1 Apache Phoenix read process 9 2.4.2 Apache Phoenix write process 12 CHAPTER 3 SYSTEM IMPLEMENTATION 14 3.1 New SQL Expression Operator for SELECT 14 3.2 Operator Implementation 16 3.2.1 Add new token and grammar rule 16 3.2.2 Traverse parse tree and generate an expression tree 18 3.2.3 Issue 18 3.2.4 Solution 19 3.2.5 Operator Algorithm 19 3.3 Add JSON data type, and modify insert Data path 24 3.3.1 JSON data type 24 3.3.2 Modify insert select Data path 25 CHAPTER 4 EVALUATION 26 4.1 System Deployment 26 4.2 Experiment 26 CHAPTER 5 SUMMARY AND FUTURE WORK 29 REFERENCES 30

    [1] J Liu, Zhen Hua, Beda Hammerschmidt, and Doug McMahon. "JSON data management: supporting schema-less development in RDBMS." Proceedings of the 2014 ACM SIGMOD international conference on Management of data. ACM, 2014.
    [2] REST. https://zh.wikipedia.org/wiki/REST
    [3] MongoDB. https://www.mongodb.org/
    [4] Apache Hadoop. https://hadoop.apache.org/
    [5] Apache HBase. http://hbase.apache.org/
    [6] Apache Phoenix. https://phoenix.apache.org/
    [7] JSON. http://json.org/
    [8] Apache Phoenix github. https://github.com/apache/phoenix
    [9] Coprocessor Introduction.https://blogs.apache.org/hbase/entry/coprocessor_introduction
    [10] ANTLR. http://www.antlr.org/
    [11] JSON in Oracle Database. http://docs.oracle.com/database/121/ADXDB/json.htm
    [12] JSON Operators in PostgreSQL. http://www.postgresql.org/docs/9.4/static/functions-json.html
    [13] Apache Hive. https://hive.apache.org/
    [14] JACKSON. https://github.com/FasterXML/jackson

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