Partitioning of Relational Databases (05) (Phân vùng cơ sở dữ liệu quan hệ)
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Slide bài giảng môn Big Data Analytics, phần B.2 Phân vùng cơ sở dữ liệu quan hệ (Partitioning of Relational Databases), trình bày bởi Lars Schmidt-Thieme tại Đại học Hildesheim.
- ドキュメント名
- Partitioning of Relational Databases (05) (Phân vùng cơ sở dữ liệu quan hệ)
- 学校 / コース
- University of Hildesheim · Big Data
- 著者（ドキュメント内）
- Lars Schmidt-Thieme
- 内容
- Tài liệu về phân vùng cơ sở dữ liệu quan hệ trong phân tích dữ liệu lớn
- 目次
- 0. Introduction
- A. Parallel Computing
- B. Distributed Storage
- C. Distributed Computing Environments
- D. Distributed Machine Learning Algorithms
- ページ数
- 47 ページ
- アップロード者
- Uni24h
説明
Trích nội dung tài liệu
Big Data Analytics Big Data Analytics B. Distributed Storage / B.2 Partioning of Relational Databases Lars Schmidt-Thieme Information Systems and Machine Learning Lab (ISMLL) Institute for Computer Science University of Hildesheim, Germany Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany 1 / 33 Big Data Analytics Syllabus Tue. 9.4. (1) 0. Introduction Tue. 16.4. Tue. 23.4. Tue. 30.4. (2) (3) (4) A. Parallel Computing A.1 Threads A.2 Message Passing Interface (MPI) A.3 Graphical Processing Units (GPUs) Tue. 7.5. Tue. 14.5. Tue. 21.5. (5) (6) (7) B. Distributed Storage B.1 Distributed File Systems B.2 Partioning of Relational Databases B.3 NoSQL Databases Tue. 28.5. Tue. 4.6. Tue. 11.6. Tue. 18.6. (8) (9) (10) C. Distributed Computing Environments C.1 Map-Reduce Pentecoste Break — C.2 Resilient Distributed Datasets (Spark) C.3 Computational Graphs (TensorFlow) Tue. 25.6. Tue. 2.7. (11) (12) D. Distributed Machine Learning Algorithms D.1 Distributed Stochastic Gradient Descent D.2 Distributed Matrix Factorization Tue. 9.7. (13) Questions and Answers Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany 1 / 33 Big Data Analytics Outline 1. Introduction 2. Horizontal Partitioning 3. Horizontal Partitioning / Parallel Query Processing 4. Vertical Partitioning 5. Sparse Data in Relational Databases Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany 1 / 33 Big Data Analytics 1. Introduction Outline 1. Introduction 2. Horizontal Partitioning 3. Horizontal Partitioning / Parallel Query Processing 4. Vertical Partitioning 5. Sparse Data in Relational Databases Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany 1 / 33 Big Data Analytics 1. Introduction Replication and Partitioning I traditionally, relational da
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Partitioning of Relational Databases (05) (Phân vùng cơ sở dữ liệu quan hệ)
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Trích nội dung tài liệu
Big Data Analytics Big Data Analytics B. Distributed Storage / B.2 Partioning of Relational Databases Lars Schmidt-Thieme Information Systems and Machine Learning Lab (ISMLL) Institute for Computer Science University of Hildesheim, Germany Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany 1 / 33 Big Data Analytics Syllabus Tue. 9.4. (1) 0. Introduction Tue. 16.4. Tue. 23.4. Tue. 30.4. (2) (3) (4) A. Parallel Computing A.1 Threads A.2 Message Passing Interface (MPI) A.3 Graphical Processing Units (GPUs) Tue. 7.5. Tue. 14.5. Tue. 21.5. (5) (6) (7) B. Distributed Storage B.1 Distributed File Systems B.2 Partioning of Relational Databases B.3 NoSQL Databases Tue. 28.5. Tue. 4.6. Tue. 11.6. Tue. 18.6. (8) (9) (10) C. Distributed Computing Environments C.1 Map-Reduce Pentecoste Break — C.2 Resilient Distributed Datasets (Spark) C.3 Computational Graphs (TensorFlow) Tue. 25.6. Tue. 2.7. (11) (12) D. Distributed Machine Learning Algorithms D.1 Distributed Stochastic Gradient Descent D.2 Distributed Matrix Factorization Tue. 9.7. (13) Questions and Answers Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany 1 / 33 Big Data Analytics Outline 1. Introduction 2. Horizontal Partitioning 3. Horizontal Partitioning / Parallel Query Processing 4. Vertical Partitioning 5. Sparse Data in Relational Databases Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany 1 / 33 Big Data Analytics 1. Introduction Outline 1. Introduction 2. Horizontal Partitioning 3. Horizontal Partitioning / Parallel Query Processing 4. Vertical Partitioning 5. Sparse Data in Relational Databases Lars Schmidt-Thieme, Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Germany 1 / 33 Big Data Analytics 1. Introduction Replication and Partitioning I traditionally, relational da
- ドキュメント名
- Partitioning of Relational Databases (05) (Phân vùng cơ sở dữ liệu quan hệ)
- 学校 / コース
- University of Hildesheim · Big Data
- 著者（ドキュメント内）
- Lars Schmidt-Thieme
- 内容
- Tài liệu về phân vùng cơ sở dữ liệu quan hệ trong phân tích dữ liệu lớn
- 目次
- 0. Introduction
- A. Parallel Computing
- B. Distributed Storage
- C. Distributed Computing Environments
- D. Distributed Machine Learning Algorithms
- ページ数
- 47 ページ
- アップロード者
- Uni24h
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