CS6530 Lab 3: SimpleDB Operators

Assigned: Wednesday October 18, 2017
Due: Friday, November 3, 5PM. 2017

In this lab assignment, you will write a set of operators for SimpleDB to implement table modifications (e.g., insert and delete records), selections, joins, and aggregates. These will build on top of the foundation that you wrote in Lab 1 to provide you with a database system that can perform simple queries over multiple tables.

Additionally, you will also utilize the buffer eviction code you have developed from your lab 3. You do not need to implement transactions or locking in this lab.

The remainder of this document gives some suggestions about how to start coding, describes a set of exercises to help you work through the lab, and discusses how to hand in your code. This lab requires you to write a fair amount of code, so we encourage you to start early!

1. Getting started

You should begin with the code you submitted for Lab 1 and Lab 2 (if you did not submit code for Lab 1 and Lab 2, or your solution didn't work properly, contact us to discuss options). We have provided you with extra test cases for this lab that are not in the original code distribution you received. We reiterate that the unit tests we provide are to help guide your implementation along, but they are not intended to be comprehensive or to establish correctness.

You will need to add these new test cases to your release. The easiest way to do this is to untar the new code in the same directory as your top-level simpledb directory, as follows:

Make a backup of your Lab 1/Lab 2 solution by typing :

$ tar -cvzf cs6530-lab2-submitted.tar.gz CS6530-lab2

Change to the directory that contains your top-level simpledb code:

$ cd CS6530-lab2

Download the new tests and skeleton code for Lab 3 from CS6530-lab3-supplement.tar.gz:
```
$ wget http://www.cs.utah.edu/~lifeifei/cs6530/CS6530-lab3-supplement.tar.gz
```
Extract the new files for Lab 3 by typing:
```
tar -xvzf CS6530-lab3-supplement.tar.gz
```
Eclipse users will have to take one more step for their code to compile. (First, make sure the project is in your workspace in Eclipse following similar steps as done in lab1.) Under the package explorer, right click the project name (probably CS6540-lab2), and select Properties. Choose Java Build Path on the left-hand-side, and click on the Libraries tab on the right-hand-side. Push the Add JARs... button, select zql.jar and jline-0.9.94.jar, and push OK, followed by OK. You may have already done this step from Lab 2; in that case you can ignore this step . Your code should now compile.

1.3. Implementation hints

As before, we strongly encourage you to read through this entire document to get a feel for the high-level design of SimpleDB before you write code.

We suggest exercises along this document to guide your implementation, but you may find that a different order makes more sense for you. As before, we will grade your assignment by looking at your code and verifying that you have passed the test for the ant targets test and systemtest. See Section 3.4 for a complete discussion of grading and list of the tests you will need to pass.

Here's a rough outline of one way you might proceed with your SimpleDB implementation; more details on the steps in this outline, including exercises, are given in Section 2 below.

Implement the operators Filter and Join and verify that their corresponding tests work. The Javadoc comments for these operators contain details about how they should work. We have given you implementations of Project and OrderBy which may help you understand how other operators work.
Implement IntegerAggregator and StringAggregator. Here, you will write the logic that actually computes an aggregate over a particular field across multiple groups in a sequence of input tuples. Use integer division for computing the average, since SimpleDB only supports integers. StringAggegator only needs to support the COUNT aggregate, since the other operations do not make sense for strings.
Implement the Aggregate operator. As with other operators, aggregates implement the DbIterator interface so that they can be placed in SimpleDB query plans. Note that the output of an Aggregate operator is an aggregate value of an entire group for each call to next(), and that the aggregate constructor takes the aggregation and grouping fields.
Implement the methods related to tuple insertion, deletion, and page eviction in BufferPool. You do not need to worry about transactions at this point.
Implement the Insert and Delete operators. Like all operators, Insert and Delete implement DbIterator, accepting a stream of tuples to insert or delete and outputting a single tuple with an integer field that indicates the number of tuples inserted or deleted. These operators will need to call the appropriate methods in BufferPool that actually modify the pages on disk. Check that the tests for inserting and deleting tuples work properly.
Note that SimpleDB does not implement any kind of consistency or integrity checking, so it is possible to insert duplicate records into a file and there is no way to enforce primary or foreign key constraints.

At this point you should be able to pass all of the tests in the ant systemtest target, which is the goal of this lab.

You'll also be able to use the provided SQL parser to run SQL queries against your database! See Section 2.6 for a brief tutorial and a description of an optional contest to see who can write the fastest SimpleDB implementation.

Finally, you might notice that the iterators in this lab extend the Operator class instead of implementing the DbIterator interface. Because the implementation of next/hasNext is often repetitive, annoying, and error-prone, Operator implements this logic generically, and only requires that you implement a simpler readNext. Feel free to use this style of implementation, or just implement the DbIterator interface if you prefer. To implement the DbIterator interface, remove extends Operator from iterator classes, and in its place put implements DbIterator.

2. SimpleDB Architecture and Implementation Guide

2.1. Filter and Join

Recall that SimpleDB DbIterator classes implement the operations of the relational algebra. You will now implement two operators that will enable you to perform queries that are slightly more interesting than a table scan.

Filter: This operator only returns tuples that satisfy a Predicate that is specified as part of its constructor. Hence, it filters out any tuples that do not match the predicate.
Join: This operator joins tuples from its two children according to a JoinPredicate that is passed in as part of its constructor. We require a simple nested loops join implementation and a hash join implementation respectively, but you may explore more interesting join implementations. Describe your implementation in your lab writeup.

Exercise 1. Implement the skeleton methods in:

src/simpledb/Predicate.java
src/simpledb/JoinPredicate.java
src/simpledb/Filter.java
src/simpledb/Join.java
src/simpledb/HashEquiJoin.java

At this point, your code should pass the unit tests in PredicateTest, JoinPredicateTest, FilterTest, JoinTest, and HashEquiJoinTest. Furthermore, you should be able to pass the system tests FilterTest, JoinTest and HashEquiJoinTest.

2.2. Aggregates

An additional SimpleDB operator implements basic SQL aggregates with a GROUP BY clause. You should implement the five SQL aggregates (COUNT, SUM, AVG, MIN, MAX) and support grouping. You only need to support aggregates over a single field, and grouping by a single field.

In order to calculate aggregates, we use an Aggregator interface which merges a new tuple into the existing calculation of an aggregate. The Aggregator is told during construction what operation it should use for aggregation. Subsequently, the client code should call Aggregator.mergeTupleIntoGroup() for every tuple in the child iterator. After all tuples have been merged, the client can retrieve a DbIterator of aggregation results. Each tuple in the result is a pair of the form (groupValue, aggregateValue), unless the value of the group by field was Aggregator.NO_GROUPING, in which case the result is a single tuple of the form (aggregateValue).

Note that this implementation requires space linear in the number of distinct groups. For the purposes of this lab, you do not need to worry about the situation where the number of groups exceeds available memory.

Exercise 2. Implement the skeleton methods in:

src/simpledb/IntegerAggregator.java
src/simpledb/StringAggregator.java
src/simpledb/Aggregate.java

At this point, your code should pass the unit tests IntegerAggregatorTest, StringAggregatorTest, and AggregateTest. Furthermore, you should be able to pass the AggregateTest system test.

2.3. HeapFile Mutability

Now, we will begin to implement methods to support modifying tables. We begin at the level of individual pages and files. There are two main sets of operations: adding tuples and removing tuples.

Removing tuples: To remove a tuple, you will need to implement deleteTuple. Tuples contain RecordIDs which allow you to find the page they reside on, so this should be as simple as locating the page a tuple belongs to and modifying the headers of the page appropriately.

Adding tuples: The insertTuple method in HeapFile.java is responsible for adding a tuple to a heap file. To add a new tuple to a HeapFile, you will have to find a page with an empty slot. If no such pages exist in the HeapFile, you need to create a new page and append it to the physical file on disk. You will need to ensure that the RecordID in the tuple is updated correctly.

Exercise 3. Implement the remaining skeleton methods in:

src/simpledb/HeapPage.java
src/simpledb/HeapFile.java
(Note that you do not necessarily need to implement writePage at this point).

To implement HeapPage, you will need to modify the header bitmap for methods such as insertTuple() and deleteTuple(). You may find that the getNumEmptySlots() and isSlotUsed() methods we asked you to implement in Lab 1 serve as useful abstractions. Note that there is a markSlotUsed method provided as an abstraction to modify the filled or cleared status of a tuple in the page header.

Note that it is important that the HeapFile.insertTuple() and HeapFile.deleteTuple() methods access pages using the BufferPool.getPage() method; otherwise, your implementation of transactions in the next lab will not work properly.

Implement the following skeleton methods in src/simpledb/BufferPool.java:

insertTuple()
deleteTuple()

These methods should call the appropriate methods in the HeapFile that belong to the table being modified (this extra level of indirection is needed to support other types of files — like indices — in the future).

At this point, your code should pass the unit tests in HeapPageWriteTest and HeapFileWriteTest. We have not provided additional unit tests for HeapFile.deleteTuple() or BufferPool.

2.4. Insertion and deletion

Now that you have written all of the HeapFile machinery to add and remove tuples, you will implement the Insert and Delete operators.

For plans that implement insert and delete queries, the top-most operator is a special Insert or Delete operator that modifies the pages on disk. These operators return the number of affected tuples. This is implemented by returning a single tuple with one integer field, containing the count.

Insert: This operator adds the tuples it reads from its child operator to the tableid specified in its constructor. It should use the BufferPool.insertTuple() method to do this.
Delete: This operator deletes the tuples it reads from its child operator from the tableid specified in its constructor. It should use the BufferPool.deleteTuple() method to do this.

Exercise 4. Implement the skeleton methods in:

src/simpledb/Insert.java
src/simpledb/Delete.java

At this point, your code should pass the unit tests in InsertTest. We have not provided unit tests for Delete. Furthermore, you should be able to pass the InsertTest and DeleteTest system tests.

2.5. Query walkthrough

The following code implements a simple join query between two tables, each consisting of three columns of integers. (The file some_data_file1.dat and some_data_file2.dat are binary representation of the pages from this file). This code is equivalent to the SQL statement:

SELECT * 
  FROM some_data_file1, some_data_file2 
  WHERE some_data_file1.field1 = some_data_file2.field1
  AND some_data_file1.id > 1

For more extensive examples of query operations, you may find it helpful to browse the unit tests for joins, filters, and aggregates.

package simpledb;
import java.io.*;

public class jointest {

    public static void main(String[] argv) {
        // construct a 3-column table schema
        Type types[] = new Type[]{ Type.INT_TYPE, Type.INT_TYPE, Type.INT_TYPE };
        String names[] = new String[]{ "field0", "field1", "field2" };

        TupleDesc td = new TupleDesc(types, names);

        // create the tables, associate them with the data files
        // and tell the catalog about the schema  the tables.
        HeapFile table1 = new HeapFile(new File("some_data_file1.dat"), td);
        Database.getCatalog().addTable(table1, "t1");

        HeapFile table2 = new HeapFile(new File("some_data_file2.dat"), td);
        Database.getCatalog().addTable(table2, "t2");

        // construct the query: we use two SeqScans, which spoonfeed
        // tuples via iterators into join
        TransactionId tid = new TransactionId();

        SeqScan ss1 = new SeqScan(tid, table1.getId(), "t1");
        SeqScan ss2 = new SeqScan(tid, table2.getId(), "t2");

        // create a filter for the where condition
        Filter sf1 = new Filter(
                                new Predicate(0,
                                Predicate.Op.GREATER_THAN, new IntField(1)),  ss1);

        JoinPredicate p = new JoinPredicate(1, Predicate.Op.EQUALS, 1);
        Join j = new Join(p, sf1, ss2);

        // and run it
        try {
            j.open();
            while (j.hasNext()) {
                Tuple tup = j.next();
                System.out.println(tup);
            }
            j.close();
            Database.getBufferPool().transactionComplete(tid);

        } catch (Exception e) {
            e.printStackTrace();
        }

    }

}

Both tables have three integer fields. To express this, we create a TupleDesc object and pass it an array of Type objects indicating field types and String objects indicating field names. Once we have created this TupleDesc, we initialize two HeapFile objects representing the tables. Once we have created the tables, we add them to the Catalog. (If this were a database server that was already running, we would have this catalog information loaded; we need to load this only for the purposes of this test).

Once we have finished initializing the database system, we create a query plan. Our plan consists of two SeqScan operators that scan the tuples from each file on disk, connected to a Filter operator on the first HeapFile, connected to a Join operator that joins the tuples in the tables according to the JoinPredicate. In general, these operators are instantiated with references to the appropriate table (in the case of SeqScan) or child operator (in the case of e.g., Join). The test program then repeatedly calls next on the Join operator, which in turn pulls tuples from its children. As tuples are output from the Join, they are printed out on the command line.

2.6. Query Parser and Contest

We've provided you with a query parser for SimpleDB that you can use to write and run SQL queries against your database once you have completed the exercises in this lab.

The first step is to create some data tables and a catalog. Suppose you have a file data.txt with the following contents:

1,10
2,20
3,30
4,40
5,50
5,50

You can convert this into a SimpleDB table using the convert command (make sure to type ant first!):

java -jar dist/simpledb.jar convert data.txt 2 "int,int"

This creates a file data.dat. In addition to the table's raw data, the two additional parameters specify that each record has two fields and that their types are int and int.

Next, create a catalog file, catalog.txt, with the follow contents:

data (f1 int, f2 int)

This tells SimpleDB that there is one table, data (stored in data.dat) with two integer fields named f1 and f2.

Finally, invoke the parser. You must run java from the command line (ant doesn't work properly with interactive targets.) From the simpledb/ directory, type:

java -jar dist/simpledb.jar parser catalog.txt

You should see output like:

Added table : data with schema INT(f1), INT(f2), 
SimpleDB>

Finally, you can run a query:

SimpleDB> select d.f1, d.f2 from data d;
Started a new transaction tid = 1221852405823
 ADDING TABLE d(data) TO tableMap
     TABLE HAS  tupleDesc INT(d.f1), INT(d.f2), 
1       10
2       20
3       30
4       40
5       50
5       50

 6 rows.
----------------
0.16 seconds

SimpleDB>

The parser is relatively full featured (including support for SELECTs, INSERTs, DELETEs, and transactions), but does have some problems and does not necessarily report completely informative error messages. Here are some limitations to bear in mind:

You must preface every field name with its table name, even if the field name is unique (you can use table name aliases, as in the example above, but you cannot use the AS keyword.)
Nested queries are supported in the WHERE clause, but not the FROM clause.
No arithmetic expressions are supported (for example, you can't take the sum of two fields.)
At most one GROUP BY and one aggregate column are allowed.
Set-oriented operators like IN, UNION, and EXCEPT are not allowed.
Only AND expressions in the WHERE clause are allowed.
UPDATE expressions are not supported.
The string operator LIKE is allowed, but must be written out fully (that is, the Postgres tilde [~] shorthand is not allowed.)

Contest

We will announce the winners in class.

We have built a SimpleDB-encoded version of the DBLP database; the needed files are located at: dblp_data.tar.gz

You should download the file and unpack it. It will create four files in the dblp_data directory. Move them into the simpledb/dataset directory. The following commands will acomplish this, if you run them from the simpledb directory:

mkdir dataset
cd dataset
wget http://www.cs.utah.edu/~lifeifei/cs6530/dblp_data.tar.gz
tar xvzf dblp_data.tar.gz
mv dblp_data/* .
rm -r dblp_data.tar.gz dblp_data

You can then run the parser with:

java -jar dist/simpledb.jar parser dataset/dblp_simpledb.schema

Or, you can simply use the script startSequential.sh provided in the Lab 3 distribution under the /bin folder:

cd bin
chmod 755 startSequential.sh
./startSequential.sh ../dataset/dblp_simpledb.schema

We will give a prize to the submission that has shortest total runtime for the following three queries (where total runtime is the sum of the runtime of each of the individual queries):

SELECT p.title
FROM papers p
WHERE p.title LIKE 'selectivity';

SELECT p.title, v.name
FROM papers p, authors a, paperauths pa, venues v
WHERE a.name = 'E. F. Codd'
AND pa.authorid = a.id
AND pa.paperid = p.id
AND p.venueid = v.id;

SELECT a2.name, count(p.id)
FROM papers p, authors a1, authors a2, paperauths pa1, paperauths pa2
WHERE a1.name = 'Michael Stonebraker'
AND pa1.authorid = a1.id 
AND pa1.paperid = p.id 
AND pa2.authorid = a2.id 
AND pa1.paperid = pa2.paperid
GROUP BY a2.name
ORDER BY a2.name;

Note that each query will print out its runtime after it executes.

You may wish to create optimized implementations of some of the operators; in particular, a fast join operator (e.g., not nested loops) will be essential for good performance on queries 2 and 3.

There is currently no optimizer in the parser, so the queries above have been written to cause the parser generate reasonable plans. Here are some helpful hints about how the parser works that you may wish to exploit while running these queries:

The table on the left side of the joins in these queries is passed in as the first DbIterator parameter to Join.
Expressions in the WHERE clause are added to the plan from top to bottom, such that first expression will be the bottom-most operator in the generated query plan. For example, the generated plan for Query 2 is:
```
Project(Join(Join(Filter(a),pa),p))
```

Our reference implementation can run Query 1 in about .35 seconds, Query 2 in about 1.5 seconds, and Query 3 in about 3.75 seconds. We implemented a special-purpose join operator for equality joins but did little else to optimize performance.

3. Logistics

You must submit your code (see below) as well as a short (2 pages, maximum) writeup describing your approach. This writeup should:

Describe any design decisions you made, including your choice of page eviction policy. If you used something other than a nested-loops join, describe the tradeoffs of the algorithm you chose.
Discuss and justify any changes you made to the API.
Describe any missing or incomplete elements of your code.
Describe how long you spent on the lab, and whether there was anything you found particularly difficult or confusing.

3.1. Collaboration

Please indicate clearly who you worked with, if anyone, on your writeup.

3.2. Submitting your assignment

Please also submit your writeup as a PDF or plain text file (.txt). Please do not submit a .doc or .docx. Use the same submission procedure as before.

Make sure your code is packaged so the instructions outlined in section 3.4 work.

3.3. Submitting a bug

SimpleDB is a relatively complex piece of code. It is very possible you are going to find bugs, inconsistencies, and bad, outdated, or incorrect documentation, etc.

We ask you, therefore, to do this lab with an adventurous mindset. Don't get mad if something is not clear, or even wrong; rather, try to figure it out yourself or send us a friendly email. Please submit (friendly!) bug reports to either the TAs or the instructor. When you do, please try to include:

A description of the bug.
A .java file we can drop in the test/simpledb directory, compile, and run.
A .txt file with the data that reproduces the bug. We should be able to convert it to a .dat file using HeapFileEncoder.

You can also post on the class page on canvass if you feel you have run into a bug.

3.4 Grading

80% of your grade will be based on whether or not your code passes the system test suite we will run over it. These tests will be a superset of the tests we have provided. Before handing in your code, you should make sure it produces no errors (passes all of the tests) from both ant test and ant systemtest.

Important: before testing, we will replace your build.xml, HeapFileEncoder.java, and the entire contents of the test/ directory with our version of these files! This means you cannot change the format of .dat files! You should therefore be careful changing our APIs. This also means you need to test whether your code compiles with our test programs. In other words, we will untar your tarball, replace the files mentioned above, compile it, and then grade it. It will look roughly like this:

[replace build.xml, HeapFileEncoder.java, and test]
$ ant test
$ ant systemtest
[additional tests]

If any of these commands fail, we'll be unhappy, and, therefore, so will your grade.

An additional 20% of your grade will be based on the quality of your writeup and our subjective evaluation of your code.

We've had a lot of fun designing this assignment, and we hope you enjoy hacking on it!