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Study of Data Size Changing Effect on Performance of Cloud, Hybrid, And Traditional DBMSs

دراسة تأثير تغير حجم البيانات على أداء نظم إدارة قواعد البيانات السحابية و الهجينة و التقليدية

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 Publication date 2015
and research's language is العربية
 Created by Shamra Editor




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With the rapid growth of the size of the data stored in the cloud systems, the need for effective data processing becomes critical and urgent. This research introduces a study of the most important characteristics of databases management systems: Hive, SQLMR, and MariaDB Galera. Hive is a cloud database management system. SQLMR is a hybrid system, which depends on the integration between the cloud and traditional systems capabilities. While MariaDB Galera is a traditional database management system developed to cope with the cloud characteristics. In this research, we show the most important developments that have been on those systems, and then we compare their performance in data processing based on the execution time of query operations with the change of the volume of data. That is to identify the performance of those systems practically and to know the developing requirements for access to optimized data management system, and to help users in the selection of the database system that achieves their requirements in terms of availability and scalability.


Artificial intelligence review:
Research summary
تتناول هذه الدراسة تأثير تغير حجم البيانات على أداء نظم إدارة قواعد البيانات السحابية والهجينة والتقليدية. تم تحليل ومقارنة أداء ثلاثة نظم رئيسية: Hive كنظام سحابي، SQLMR كنظام هجين يجمع بين القدرات السحابية والتقليدية، وMariaDB Galera كنظام تقليدي مطور لدعم الخصائص السحابية. تم قياس أداء هذه النظم من خلال زمن تنفيذ عمليات الاستعلام مع تغير حجم البيانات، بهدف تحديد الأداء العملي لهذه النظم وتقديم توصيات لتطويرها للوصول إلى نظام إدارة بيانات أمثل. أظهرت النتائج تفوق الأنظمة السحابية والهجينة على الأنظمة التقليدية من حيث سرعة تنفيذ الاستعلامات، مع تقارب أداء Hive وSQLMR بشكل كبير. كما أظهرت الدراسة تفوق MariaDB Galera باستخدام Shard-Query على MySQL في معالجة البيانات الكبيرة. تم تقديم توصيات لتحسين أداء الأنظمة السحابية من خلال تطبيق خوارزميات أمثلة وتحسين طريقة عمل MapReduce.
Critical review
تقدم هذه الدراسة مقارنة شاملة ومفصلة بين نظم إدارة قواعد البيانات المختلفة، مما يوفر فهماً عميقاً لأداء هذه النظم مع تغير حجم البيانات. ومع ذلك، يمكن أن تكون الدراسة أكثر شمولاً إذا تضمنت تحليلًا لتأثير عوامل أخرى مثل التكاليف التشغيلية والأمان. كما أن التركيز على تحسينات محددة في خوارزميات MapReduce يمكن أن يكون مفيدًا لتقديم حلول عملية لتحسين الأداء. من الجيد أيضًا تضمين دراسة حالات عملية لتطبيق هذه النظم في بيئات حقيقية لمعرفة مدى توافق النتائج مع الواقع العملي.
Questions related to the research
  1. ما هي النظم الثلاثة التي تم تحليلها في الدراسة؟

    النظم الثلاثة هي Hive كنظام سحابي، SQLMR كنظام هجين، وMariaDB Galera كنظام تقليدي مطور لدعم الخصائص السحابية.

  2. ما هو الهدف الرئيسي من هذه الدراسة؟

    الهدف الرئيسي هو تحديد أداء نظم إدارة قواعد البيانات المختلفة مع تغير حجم البيانات وتقديم توصيات لتطويرها للوصول إلى نظام إدارة بيانات أمثل.

  3. ما هي النتائج الرئيسية التي توصلت إليها الدراسة؟

    أظهرت النتائج تفوق الأنظمة السحابية والهجينة على الأنظمة التقليدية من حيث سرعة تنفيذ الاستعلامات، مع تقارب أداء Hive وSQLMR بشكل كبير. كما أظهرت الدراسة تفوق MariaDB Galera باستخدام Shard-Query على MySQL في معالجة البيانات الكبيرة.

  4. ما هي التوصيات التي قدمتها الدراسة لتحسين أداء الأنظمة السحابية؟

    قدمت الدراسة توصيات لتحسين أداء الأنظمة السحابية من خلال تطبيق خوارزميات أمثلة وتحسين طريقة عمل MapReduce.


References used
MELL, P.; GRANCE, T., The NIST Definition of Cloud Computing. NIST Special Publication 800-145, September 2011
SADASHIV,N.; KUMAR, S. M.D., Cluster, Grid and Cloud Computing: A Detailed Comparison, The 6th International Conference on Computer Science & Education, SuperStar Virgo, Singapore (ICCSE 2011) August 3-5, 2011
FURHT, B.; ESCALANTE, A., Hand Book of Cloud Computing. Springer, 2010, pp: 3-45
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