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<!DOCTYPE html>
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<head>
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<title>Traditional vs. Modern Database Systems</title>
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<h2 id="cmpt843">CMPT 843: Traditional vs. Modern Database Systems (SFU, Spring 2019)</h2>
<h3 id="motivation">Motivation</h3>
<p>The Big Data movement is attracting an increasing number of new researchers to work on data processing related research. On the other hand, the database community has been thinking about how to address data-processing challenges for over 40 years. Numerous elegant ideas were proposed in the past and many of them are being widely applied in industry. Therefore, there is a high need to educate new researchers to learn classical database knowledge and make sure they can stand on the shoulders of giants rather than reinvent the wheel.</p>
<h3 id="topics">Topics</h3>
<p>Because of the purpose above, the course will be divided into two parts.</p>
<ol>
<li>The first part will guide students to read classical database papers that were published before 2000 on the topics including Data Model, Relational Database Systems, Transaction Management, Query Optimization, Data Warehouse, and Approximate Query Processing. </li>
<li>The second part will be mostly about the papers published in the recent ten years on the topics including MapReduce, Spark, Column Store, NoSQL, NewSQL, and ML over SQL. </li>
</ol>
<h3 id="objectives">Objectives</h3>
<p>Through this traditional vs. modern view of data processing, the students should gain a much deeper understanding of the Big Data movement and form their own opinion on what's novel about Big Data systems.</p>
<p>Furthermore, since this is a graduate seminar, another important objective is to train students to master basic skills for being a researcher. The course will create a number of opportunities for students to learn how to read a paper, how to write a paper review, how to give a good research talk, and how to ask questions during a talk?
</p>
<h3 id="logistics">Logistics</h3>
<ul>
<li><b>Instructor: </b><a href="http://cs.sfu.ca/~jnwang/">Jiannan Wang</a></li>
<li><b>Time: </b>Tuesday, 1:00pm - 2:20pm; Thursday, 1:00pm - 2:20pm</li>
<li><b>Location: </b>AQ5037</li>
<li><b>Office Hours: </b>By appointment. <a href="mailto:[email protected]">E-mail me</a> to book a slot</li>
</ul>
<h3 id="pre-requisites">Pre-requisites</h3>
<ul>
<li> Students should have taken undergraduate Database Systems courses (See <a href="https://portal.cs.sfu.ca/portal/outlines/1171-CMPT-354-D100/">CMPT 354</a> and <a href="https://portal.cs.sfu.ca/portal/outlines/1171-CMPT-454-D100/">CMPT 454</a> course outlines)</li>
</ul>
<h3 id="grading">Grading</h3>
<ul>
<li>Paper Presentation: 20% </li>
<li>Questions: 10%</li>
<li>Paper Review: 20%</li>
<li>Participation: 10%</li>
<li>Blog Post: 10%</li>
<li>Final Project: 30% (2% plan + 14% poster + 14% report)</li>
</ul>
<!--
<h3 id="schedule">Schedule</h3>
<table class="table table-bordered">
<thead>
<tr class="info">
<td><b>Date</b></td>
<td><b>Topic</b></td>
<td><b>Content</b></td>
<td><b>Presenter</b></td>
</tr>
</thead>
<tbody>
<tr>
<td>Th 1/3</td>
<td>Course Objective I</td>
<td> Course Introduction and History of Database Systems</td>
<td> Jiannan [<a href="Lectures/intro.pdf">slides</a>]</td>
</tr>
<tr class="active">
<td>Tu 1/8 </td>
<td>Course Objective II</td>
<td> Essential Skills Needed for a PhD Student (How to <a href='https://sfu-db.github.io/cmpt884-fall16/Papers/How%20to%20Read%20a%20Paper.pdf'>read</a> & <a href='https://sfu-db.github.io/cmpt884-fall16/Papers/review-writing.pdf'>review</a> a paper? How to give a <a href="https://sfu-db.github.io/cmpt884-fall16/Papers/giving-a-talk.pdf">talk?</a> How to <a href="https://www.amazon.com/Asking-Right-Questions-11th-Browne/dp/0321907957">ask</a> questions?)</td>
<td> Jiannan [<a href="Lectures/research-skills.pdf">slides</a>]</td>
</tr>
</tbody>
</table>
<tr>
<td style="vertical-align:middle">F 2/23</td>
<td rowspan="1" style="vertical-align:middle">Summary</td>
<td> <a href="https://www.youtube.com/watch?v=9K0SWs1mOD0">One Size Fits All - An Idea Whose Time Has Come and Gone (2005)</a> <br/>
<a href="https://www.youtube.com/watch?v=HEupUSSSEBo">Oracle Autonomous Database (2017)<a/>
</td>
<td> Stonebraker [<a href="https://www.youtube.com/watch?v=9K0SWs1mOD0">video</a>] <br/>
Ellison [<a href="https://www.youtube.com/watch?v=HEupUSSSEBo"> video</a>]</td>
</tr>
<h3 id="grading">Final Project</h3>
<ul>
<li> <a href="./Project/project-instruction.html">Big Data Systems</a> </li>
</ul>
-->
<h3 id="grading">Blog Post</h3>
<ul>
<li> <a href="./blog/blog-post.html">Understand Database Systems in Simple Ways</a> </li>
</ul>
<h3 id="grading">Final Project</h3>
<ul>
<li> <a href="./Project/project-instruction.html">Big Data Systems</a> </li>
</ul>
<h3 id="schedule">Schedule</h3>
<p>
<ul>
<li><mark>If you are a speaker, please see <a href="https://docs.google.com/document/d/16SnmjVV7tPULGl6e4T8zR2EhsRT63ys_-IgfMzhyq4o/edit?usp=sharing
">this doc</a> about how to upload your slides after the presentation. <mark></li>
<li><mark>If you ask any question in the Q/A sessions, please write down the questions in this <a href="https://docs.google.com/spreadsheets/d/1O_psziJwQUkpjaHJaQr6TSh-qmGVeJNWvdZWxtJN15k/edit?usp=sharing">form</a> (one question per row). You need to ask 20 questions in total (0.5 points per question) in order to get the full mark on Questions<mark></li>
</p>
</ul>
<table class="table table-bordered">
<thead>
<tr class="info">
<td><b>Date</b></td>
<td><b>Topic</b></td>
<td><b>Content</b></td>
<td><b>Presenter</b></td>
</tr>
</thead>
<tbody>
<tr>
<td>Th 1/3</td>
<td>Course Objective I</td>
<td> Course Introduction and History of Database Systems</td>
<td> Jiannan [<a href="Lectures/intro.pdf">slides</a>]</td>
</tr>
<tr class="active">
<td>Tu 1/8 </td>
<td>Course Objective II</td>
<td> Essential Skills Needed for a PhD Student (How to <a href='https://sfu-db.github.io/cmpt884-fall16/Papers/How%20to%20Read%20a%20Paper.pdf'>read</a> & <a href='https://sfu-db.github.io/cmpt884-fall16/Papers/review-writing.pdf'>review</a> a paper? How to give a <a href="https://sfu-db.github.io/cmpt884-fall16/Papers/giving-a-talk.pdf">talk?</a> How to <a href="https://www.amazon.com/Asking-Right-Questions-11th-Browne/dp/0321907957">ask</a> questions?)</td>
<td> Jiannan [<a href="Lectures/research-skills.pdf">slides</a>]</td>
</tr>
<tr class="info">
<td colspan="4" style="text-align:center"><b>Part I: Traditional Database Systems and Techniques (before 2000)</b></td>
</tr>
<tr>
<td rowspan="2" style="vertical-align:middle">Th 1/17</td>
<td rowspan="2" style="vertical-align:middle">Background</td>
<td> <a href="Papers/p110-silberschatz-background.pdf">1. Database Systems: Achievements and Opportunities (1990)</a></td>
<td> Lakshayy [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/P1.pdf'>slides</a>] </td>
</tr>
<tr>
<td> <a href="Papers/Asilomar.pdf">2. The Asilomar Report on Database Research (1998)</a></td>
<td> Inder[<a href="Lectures/Asilomar.pdf">slides</a>] </td>
</tr>
<tr class="active">
<td style="vertical-align:middle">Tu 1/22</td>
<td style="vertical-align:middle">Data Model</td>
<td> <a href="Papers/p377-codd.pdf">3. A Relational Model of Data for Large Shared Data Banks (1970)</a> <br/> <a href="Papers/datamodel.pdf">4. What Goes Around Comes Around (1960-1970, Sec I~IV only)</a> </td>
<td>Arshvir <br/> Mehvish [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/What goes around comes around.pdf'>slides</a>]</td>
</tr>
<tr>
<td style="vertical-align:middle">Th 1/24</td>
<td rowspan = "2" style="vertical-align:middle">Traditional DBMS</td>
<td> <a href="Papers/history-of-system-r.pdf">5. A History and Evaluation of System R (1981)</a><br/> <a href="Papers/postgres.pdf">6. The Design of Postgres (1986)</a> </td>
<td> Ankita [<a href="Lectures/System_R.pdf">slides</a>]<br/>
Ruijia [<a href="Lectures/TheDesignOfPostgres.pdf">slides</a>] </td>
</tr>
<tr>
<td style="vertical-align:middle">Tu 1/29</td>
<td > <a href="Papers/chaudhuri97.pdf"> 7. An Overview of Data Warehousing and OLAP Technology (1997) </a></td>
<td> Prabhjot [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/AnOverviewofDataWarehousing.pdf'>slides</a>] </td>
</tr>
<tr>
<td style="vertical-align:middle">Th 1/31</td>
<td rowspan="2" style="vertical-align:middle">Query Optimization</td>
<td> <a href="Papers/p23-selinger.pdf">8. Access Path Selection in a Relational Database Management System (1979)</a> <br/><a href="Papers/Volcano.pdf">9. The Volcano Optimizer Generator: Extensibility and Efficient Search (1993)</a> </td>
<td>Jill [<a href = 'Lectures/jill_08.pdf'>slides</a>]<br/> Ravi[<a href="Lectures/VolcanoOptimizer.pdf">slides</a>] </td>
</tr>
<tr>
<td>Tu 2/5</td>
<td> <a href="Papers/p261-avnur.pdf">10. Eddies: Continuously Adaptive Query Processing (2000)</a> </td>
<td> Ohoud [<a href="Lectures/Eddies.pdf">slides</a>] </td>
</tr>
<tr class="active">
<td style="vertical-align:middle">Th 2/7</td>
<td rowspan="2" style="vertical-align:middle">Transaction Management</td>
<td> <a href="Papers/GrayLocks.pdf">11. Granularity of Locks and Degrees of Consistency in a Shared Data Base (1976, Part 1 only)</a> <br/> <a href="Papers/GrayLocks.pdf">12. Granularity of Locks and Degrees of Consistency in a Shared Data Base (1976, Part 2 only)</a> </td>
<td>Muhammad [<a href="https://docs.google.com/presentation/d/1rXwbcu0Fqe-b_7Au0egRC3mfwMkFP65wSUt7QAwupHU/edit?usp=sharing">slides</a>] <br/> Kyle [<a href="Lectures/degrees_of_consistency.pptx">slides</a>] </td>
</tr>
<tr class="active">
<td>Tu 2/12</td>
<td> <a href="Papers/occ-tods1981.pdf">13. On Optimistic Methods for Concurrency Control (1981)</a></td>
<td> kiarash</td>
</tr>
<tr class="active">
<td style="vertical-align:middle">Th 2/14</td>
<td rowspan="1" style="vertical-align:middle">Interactive Analytics</td>
<td> <a href="Papers/cube.pdf"> 14. Data Cube: A Relational Aggregation Operator Generalizing Group-by, Cross-tab, and Sub-totals (1997)</a> <br/> <a href="Papers/p159-zhao-rolap.pdf"> 15. An Array-Based Algorithm for Simultaneous Multidimensional Aggregates (1997) </a></td>
<td>Xiaoying Wang [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/DataCube.pdf'>slides</a>] <br/> Pushkar</td>
</tr>
<tr class="info">
<td colspan="4" style="text-align:center"><b>Part II: Modern Database Systems and Techniques (After 2000)</b></td>
</tr>
<tr>
<td rowspan="2" style="vertical-align:middle">Tu 2/26</td>
<td>Background</td>
<td> <a href="Papers/bigdatawhitepaper.pdf">16. Challenges and Opportunities with Big Data (2011)</a></td>
<td>Jetic [<a href = 'https://github.com/sfu-db/dbsystems/raw/master/Lectures/Challenges%20and%20Opportunities%20with%20Big%20Data.pdf'>slides</a>] </td>
</tr>
<tr>
<td rowspan="2" style="vertical-align:middle">Column Store</td>
<td> <a href="Papers/stonebraker-cstore.pdf">17. C-store: a column-oriented DBMS (2005)</a></td>
<td>Ruijia [<a href="Lectures/C-StoreAColumn-orientedDBMS.pdf">slides</a>] </td>
</tr>
<tr>
<td style="vertical-align:middle">Th 2/28</td>
<td> <a href="Papers/dremel.pdf">18. Dremel: Interactive Analysis Of Web-Scale Datasets (2010)</a> <br/> <a href="Papers/abadi-sigmod08.pdf">19. Column-Stores vs. Row-Stores: How Different Are They Really? (2012)</a> </td>
<td>Mohan [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/Dremel.pdf'>slides</a>] <br/> Mehvish[<a href = 'https://sfu-db.github.io/dbsystems/Lectures/Column-Stores VS Row-Stores.pptx'>slides</a>]</td>
</tr>
<tr class="active">
<td >Tu 3/5</td>
<td rowspan="3" style="vertical-align:middle">MapReduce and Beyond</td>
<td> <a href="Lectures/why-mapreduce.pdf">Why Mapreduce</a> & <a href="Lectures/why-spark.pdf">Why Spark</a></td>
<td>Jiannan</td>
</tr>
<tr class="active">
<td >Th 3/7</td>
<td> <a href="Papers/mapreduce-osdi2004.pdf">20. MapReduce: Simplified Data Processing on Large Clusters (2003)</a> <br/> <a href="Papers/SIGMOD09_benchmark_dewitt_stonebraker.pdf">21. A Comparison of Approaches to Large-Scale Data Analysis (2009)</a> <br/> <a href="Lectures/parallel-db.pdf">Parallel Database</a> </td>
<td>Xiaoying [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/MapReduce.pdf'>slides</a>] <br/> Inder[<a href="Lectures/LargeScale.pdf">slides</a>]</td>
</tr>
<tr class="active">
<td>Tu 3/12</td>
<td> <a href="Papers/nsdi12-final138.pdf">22. Resilient Distributed Datasets: A Fault-tolerant Abstraction for In-memory Cluster Computing (2012)</a> <br/> <a href="Papers/SparkSQLSigmod2015.pdf">23. Spark SQL: Relational Data Processing in Spark (2015)</a> </td>
<td> Ravi[<a href="Lectures/RDDInMemory.pdf">slides</a>] <br/> Pushkar </td>
</tr>
<tr>
<td >Th 3/14</td>
<td rowspan="2" style="vertical-align:middle">NoSQL</td>
<td> OldSQL vs. NoSQL vs NewSQL <br/> <a href="Papers/bigtable-osdi06.pdf">24. Bigtable: A Distributed Storage System for Structured Data (2006)</a> <br/> </td>
<td>Jiannan <br/> Ankita [<a href="Lectures/Bigtable_PP2.pdf">slides</a>]</td>
</tr>
<tr>
<td>Tu 3/19</td>
<td> <a href="Papers/decandia07dynamo.pdf">25. Dynamo: Amazon's Highly Available Key-Value Store (2007)</a> <br/> <a href="Papers/CAP-12years.pdf">26. CAP Twelve Years Later: How the "Rules" Have Changed (2012)</a> </td>
<td> Jill [<a href = 'Lectures/jill_25(Dynamo).pdf'>slides</a>]<br/> Ohoud [<a href="Lectures/CAP.pdf">slides</a>] </td>
</tr>
<tr class="active">
<td >Th 3/21</td>
<td rowspan="2" style="vertical-align:middle">NewSQL</td>
<td> <a href="Papers/harizopoulos-2008.pdf">27. OLTP Through the Looking Glass, and What We Found There (2008)</a> <br/> <a href="Papers/Hekaton.pdf">28. Hekaton: SQL Server's Memory-optimized OLTP Engine (2013)</a> </td>
<td> Lakshayy [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/OLTP_Through_the_Looking_Glass_and_What_We_Found_There.pdf'>slides</a>] <br/> Arshvir</td>
</tr>
<tr class="active">
<td>Tu 3/26</td>
<td> <a href="Papers/hyper.pdf">29. Efficiently Compiling Efficient Query Plans for Modern Hardware (2011)</a><br/> <a href="Papers/nosql_sql.pdf"> 30. Scalable SQL and NoSQL data stores (2010)</a> <br/> </td>
<td> Kyle<br/> MoHan [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/ScalableSQL.pdf'>slides</a>]</td>
</tr>
<tr>
<td style="vertical-align:middle" >Th 3/28</td>
<td rowspan="2" style="vertical-align:middle">ML and SQL</td>
<td> <a href="Papers/probpred.pdf">31. Accelerating Machine Learning Inference with Probabilistic Predicates (2018) </a> <br/> <a href="Papers/noscope.pdf">32. NoScope: Optimizing Deep CNN-Based Queries over Video Streams at Scale (2017</a> </td>
<td> Jetic [<a href = 'https://github.com/sfu-db/dbsystems/raw/master/Lectures/Accelerating%20Machine%20Learning%20Inference%20with%20Probabilistic%20Predicates.pdf'>slides</a>] <br/> Prabhjot [<a href = 'https://sfu-db.github.io/dbsystems/Lectures/NoScope.pdf'>slides</a>]</td>
</tr>
<tr>
<td style="vertical-align:middle" >Tu 4/2</td>
<td> <a href="Papers/Join-DeepRL.pdf">33. Learning to Optimize Join Queries With Deep Reinforcement Learning (2018) </a> <br/> <a href="Papers/learned-index.pdf">34. The Case for Learned Index Structures (2018)</a> </td>
<td> Muhammad [<a href="https://docs.google.com/presentation/d/1iluletxFgRoOjp9CmKgLZuKylXFYkGuzM2GG62RYAo0/edit?usp=sharing">slides</a>]<br/> Ruijia [<a href="Lectures/TheCaseForLearnedIndexStructure.pdf">slides</a>] </td>
</tr>
<tr class="info">
<td colspan="4" style="text-align:center"><b>Final Project</b></td>
</tr>
<tr>
<td>W 4/10</td>
<td>Final Project</td>
<td> Final Project Poster Session </td>
<td> Groups</td>
</tr>
</tbody>
</table>
</br>
<!--
<h3 id="papers">List of Papers</h3>
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<h4 id="part1">Part I: Traditional Database Systems and Techniques (before 2000)</h4>
<h5>Background</h5>
<ol>
<li> <a href="Papers/p110-silberschatz-background.pdf">Database Systems: Achievements and Opportunities (1990)</a> </li>
<li> <a href="Papers/Asilomar.pdf">The Asilomar Report on Database Research (1998)</a> </li>
</ol>
<h5>Data Model</h5>
<ol start="3">
<li> <a href="Papers/p377-codd.pdf">A Relational Model of Data for Large Shared Data Banks (1970)</a> </li>
<li> <a href="Papers/datamodel.pdf">What Goes Around Comes Around (1960-1970, Sec I~IV only)</a></li>
</ol>
<h5>Traditional DBMS</h5>
<ol start="5">
<li> <a href="Papers/history-of-system-r.pdf">A History and Evaluation of System R (1981)</a> </li>
<li> <a href="Papers/postgres.pdf">The Design of Postgres (1986)</a> </li>
<li> <a href="Papers/GammaDatabaseMachine.pdf">The Gamma database machine project (1990)</a></li>
<li> <a href="Papers/chaudhuri97.pdf">An Overview of Data Warehousing and OLAP Technology (1997)</a></li>
</ol>
<h5>Transaction Management</h5>
<ol start="9">
<li> <a href="Papers/GrayLocks.pdf">Granularity of Locks and Degrees of Consistency in a Shared Data Base (1976, Part 1 only)</a> </li>
<li> <a href="Papers/GrayLocks.pdf">Granularity of Locks and Degrees of Consistency in a Shared Data Base (1976, Part 2 only)</a> </li>
<li> <a href="Papers/occ-tods1981.pdf">On Optimistic Methods for Concurrency Control (1981)</a> </li>
<li> <a href="Papers/p609-agrawal.pdf">Concurrency control performance modeling: alternatives and implications (1987)</a> </li>
</ol>
<h5>Query Optimization</h5>
<ol start="13">
<li> <a href="Papers/p23-selinger.pdf">Access Path Selection in a Relational Database Management System (1979)</a> </li>
<li> <a href="Papers/Volcano.pdf">The Volcano Optimizer Generator: Extensibility and Efficient Search (1993)</a> </li>
<li> <a href="Papers/p106-kabra.pdf">Efficient mid-query re-optimization of sub-optimal query execution plans (1998)</a> </li>
<li> <a href="Papers/p261-avnur.pdf">Eddies: Continuously Adaptive Query Processing (2000)</a> </li>
</ol>
<h5>Interactive Analytics</h5>
<ol start="17">
<li> <a href="Papers/cube.pdf">Data Cube: A Relational Aggregation Operator Generalizing Group-by, Cross-tab, and Sub-totals (1997) </a> </li>
<li> <a href="Papers/p159-zhao-rolap.pdf">An Array-Based Algorithm for Simultaneous Multidimensional Aggregates (1997)</a> </li>
<li> <a href="Papers/p331-gibbons.pdf">New Sampling-Based Summary Statistics for Improving Approximate Query Answers (1998)</a> </li>
<li> <a href="Papers/online-aggregation.pdf">Informix under CONTROL: Online Query Processing (2000)</a> </li>
</ol>
<h4 id="part2">Part II: Modern Database Systems and Techniques (after 2000)</h4>
<h5>Background</h5>
<ol start="21">
<li> <a href="Papers/bigdatawhitepaper.pdf">Challenges and Opportunities with Big Data (2011)</a> </li>
</ol>
<h5>MapReduce and Beyond</h5>
<ol start="22">
<li> <a href="Papers/mapreduce-osdi2004.pdf">MapReduce: Simplified Data Processing on Large Clusters (2003)</a> </li>
<li> <a href="Papers/SIGMOD09_benchmark_dewitt_stonebraker.pdf">A Comparison of Approaches to Large-Scale Data Analysis (2009)</a></li>
<li> <a href="Papers/nsdi12-final138.pdf">Resilient Distributed Datasets: A Fault-tolerant Abstraction for In-memory Cluster Computing (2012)</a> </li>
<li> <a href="Papers/SparkSQLSigmod2015.pdf">Spark SQL: Relational Data Processing in Spark (2015)</a></li>
</ol>
<h5>Column Store</h5>
<ol start="26">
<li> <a href="Papers/stonebraker-cstore.pdf">C-store: A Column-oriented DBMS (2005)</a> </li>
<li> <a href="Papers/dremel.pdf">Dremel: Interactive Analysis Of Web-Scale Datasets (2010)</a></li>
<li><a href="Papers/abadi-sigmod08.pdf">Column-Stores vs. Row-Stores: How Different Are They
Really?(2012)</a></li>
</ol>
<h5>NoSQL</h5>
<ol start="29">
<li> <a href="Papers/paper-ton.pdf">Chord: A Scalable Peer-to-peer Lookup Protocol for Internet Applications (2003)</a> </li>
<li> <a href="Papers/bigtable-osdi06.pdf">Bigtable: A Distributed Storage System for Structured Data (2006)</a> </li>
<li><a href="Papers/decandia07dynamo.pdf">Dynamo: Amazon's Highly Available Key-Value Store (2007)</a></li>
<li> <a href="Papers/CAP-12years.pdf">CAP Twelve Years Later: How the "Rules" Have Changed (2012)</a></li>
</ol>
<h5>NewSQL</h5>
<ol start="33">
<li> <a href="Papers/harizopoulos-2008.pdf">OLTP Through the Looking Glass, and What We Found There (2008)</a> </li>
<li><a href="Papers/Hekaton.pdf">Hekaton: SQL Server's Memory-optimized OLTP Engine (2013)</a></li>
<li> <a href="Papers/hyper.pdf">Efficiently Compiling Efficient Query Plans for Modern Hardware (2011)</a></li>
<li> <a href="Papers/Datastores.pdf">Scalable SQL and NoSQL data stores (2010)</a></li>
</ol>
<h5>ML and SQL</h5>
<ol start="37">
<li><a href="Papers/probpred.pdf">Accelerating Machine Learning Inference with Probabilistic Predicates (2018)</a></li>
<li><a href="Papers/noscope.pdf">NoScope: Optimizing Deep CNN-Based Queries over Video Streams at Scale (2017)</a></li>
<li><a href="Papers/Join-DeepRL.pdf">Learning to Optimize Join Queries With Deep Reinforcement Learning (2018)</a></li>
<li><a href="Papers/learned-index.pdf">The Case for Learned Index Structures (2018)</a></li>
</ol>
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<h3 id="references">References</h3>
<ul>
<li><a href="http://www.redbook.io/">Redbook - 5th Edition (Peter Bailis, Joseph M. Hellerstein, Michael Stonebraker)</a> </li>
<li><a href="https://github.com/rxin/db-readings">Readings in Database (Reynold Xin) </a> </li>
<li><a href="https://sites.google.com/site/cs286fall2014/">CS286: Implementation of Database Systems (UC Berkeley, Fall 2014)</a> </li>
<li><a href="http://web.eecs.umich.edu/~mozafari/fall2015/eecs584/">EECS 584: Advanced Database Management Systems (UMichgan, 2015 Fall)</a> </li>
<li><a href="http://columbia.github.io/systems-bigdata-class/">Big Data Systems (Columbia, 2016 Spring)</a> </li>
<li><a href="http://www.cs.cmu.edu/~pavlo/courses/fall2013/">15-799: Advanced Topics in Database Systems (CMU, 2013 Fall)</a> </li>
</ul>
<div class="row"><h4> </h4><hr><p class="text-center"> © Jiannan Wang 2019</p></div>
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