Assigned: Monday, September 22, 2014
Due: Wednesday, October 1, 2014 11:59 PM EDT
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, we ignored the issue of buffer pool management in Lab 1: we have not dealt with the problem that arises when we reference more pages than we can fit in memory over the lifetime of the database. In Lab 2, you will design an eviction policy to flush stale pages from the buffer pool.
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!
You should begin with the code you submitted for Lab 1 (if you did not submit code for Lab 1, or your solution didn't work properly, contact us to discuss options). Additionally, we are providing extra source and test files for this lab that are not in the original code distribution you received.
You will need to add these new files to your release. The easiest way to do this is to change to your project directory (probably called simple-db-hw) and pull from the master GitHub repository into a new branch named lab2:
$ cd simple-db-hw
$ git checkout -b lab2
$ git pull upstream master
$ git push origin lab2
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 simple-db-hw), 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. Your code should now compile.
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
FilterandJoinand verify that their corresponding tests work. The Javadoc comments for these operators contain details about how they should work. We have given you implementations ofProjectandOrderBywhich may help you understand how other operators work. -
Implement
IntegerAggregatorandStringAggregator. 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
Aggregateoperator. As with other operators, aggregates implement theDbIteratorinterface so that they can be placed in SimpleDB query plans. Note that the output of anAggregateoperator is an aggregate value of an entire group for each call tonext(), 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
InsertandDeleteoperators. Like all operators,InsertandDeleteimplementDbIterator, 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 inBufferPoolthat 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 2.7 for a brief tutorial.
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.
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
Predicatethat 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
JoinPredicatethat is passed in as part of its constructor. We only require a simple nested loops join, 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
At this point, your code should pass the unit tests in PredicateTest, JoinPredicateTest, FilterTest, and JoinTest. Furthermore, you should be able to pass the system tests FilterTest and JoinTest.
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.
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, as well as BufferPoolWriteTest.
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
tableidspecified in its constructor. It should use theBufferPool.insertTuple()method to do this. -
Delete: This operator deletes the tuples it reads from its child operator from the
tableidspecified in its constructor. It should use theBufferPool.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.
In Lab 1, we did not correctly observe the limit on the maximum number of pages
in the buffer pool defined by the
constructor argument numPages. Now, you will choose a page eviction
policy and instrument any previous code that reads or creates pages to
implement your policy.
When more than numPages pages are in the buffer pool, one page should be evicted from the pool before the next is loaded. The choice of eviction policy is up to you; it is not necessary to do something sophisticated. Describe your policy in the lab writeup.
Notice that BufferPool asks you to implement
a flushAllPages() method. This is not something you would ever
need in a real implementation of a buffer pool. However, we need this method
for testing purposes. You should never call this method from any real code.
Because of the way we have implemented ScanTest.cacheTest, you will need to ensure that your flushPage and flushAllPages methods do no evict pages from the buffer pool to properly pass this test.
flushAllPages should call flushPage on all pages in the BufferPool, and flushPage should write any dirty page to disk and mark it as not dirty, while leaving it in the BufferPool.
The only method which should remove page from the buffer pool is evictPage, which should call flushPage on any dirty page it evicts.
Exercise 5.
Fill in the flushPage() method and additional helper
methods to implement page eviction in:
- src/simpledb/BufferPool.java
If you did not implement writePage() in
HeapFile.java above, you will also need to do that here. Finally,
you should also implement discardPage() to remove a page from the
buffer pool without flushing it to disk. We will not test discardPage()
in this lab, but it will be necessary for future labs.
At this point, your code should pass the EvictionTest system test.
Since we will not be checking for any particular eviction policy, this test works by creating a BufferPool with 16 pages (NOTE: while DEFAULT_PAGES is 50, we are initializing the BufferPool with less!), scanning a file with many more than 16 pages, and seeing if the memory usage of the JVM increases by more than 5 MB. If you do not implement an eviction policy correctly, you will not evict enough pages, and will go over the size limitation, thus failing the test.
You have now completed this lab. Good work!
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 > 1For 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.
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 following 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.)
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.
This lab should be manageable for a single person, but if you prefer to work with a partner, this is also OK. Larger groups are not allowed. Please indicate clearly who you worked with, if anyone, on your individual writeup.
You may submit your code multiple times; we will use the latest version you submit that arrives before the deadline (before 11:59 PM on the due date). Place the write-up in a file called answers.txt or answers.pdf in the top level of your simple-db-hw directory. Important: In order for your write-up to be added to the git repo, you need to explicitly add it:
$ git add answers.txtYou also need to explicitly add any other files you create, such as new *.java files.
The criteria for your lab being submitted on time is that your code must be tagged and pushed by the date and time. This means that if one of the TAs or the instructor were to open up GitHub, they would be able to see your solutions on the GitHub web page.
Just because your code has been commited on your local machine does not mean that it has been submitted; it needs to be on GitHub.
There is a bash script turnInLab2.sh in the root level directory of simple-db-hw that commits
your changes, deletes any prior tag
for the current lab, tags the current commit, and pushes the branch and tag
to GitHub. If you are using Linux or Mac OSX, you should be able to run the following:
$ ./turnInLab2.shYou should see something like the following output:
$ ./turnInLab2.sh
[master b155ba0] Lab 2
1 file changed, 1 insertion(+)
Deleted tag 'lab2' (was b26abd0)
To git@github.com:MIT-DB-Class/hw-answers-becca.git
- [deleted] lab2
Counting objects: 11, done.
Delta compression using up to 4 threads.
Compressing objects: 100% (4/4), done.
Writing objects: 100% (6/6), 448 bytes | 0 bytes/s, done.
Total 6 (delta 3), reused 0 (delta 0)
To git@github.com:MIT-DB-Class/hw-answers-becca.git
ae31bce..b155ba0 master -> master
Counting objects: 1, done.
Writing objects: 100% (1/1), 152 bytes | 0 bytes/s, done.
Total 1 (delta 0), reused 0 (delta 0)
To git@github.com:MIT-DB-Class/hw-answers-becca.git
* [new tag] lab2 -> lab2If the above command worked for you, you can skip to item 6 below. If not, submit your solutions for lab 2 as follows:
-
Look at your current repository status.
$ git status
-
Add and commit your code changes (if they aren't already added and commited).
$ git commit -a -m 'Lab 2' -
Delete any prior local and remote tag (this will return an error if you have not tagged previously; this allows you to submit multiple times)
$ git tag -d lab2 $ git push origin :refs/tags/lab2
-
Tag your last commit as the lab to be graded
$ git tag -a lab2 -m 'lab2' -
This is the most important part: push your solutions to GitHub.
$ git push origin master $ git push origin lab2
-
The last thing that we strongly recommend you do is to go to the [MIT-DB-Class] organization page on GitHub to make sure that we can see your solutions.
Just navigate to your repository and check that your latest commits are on GitHub. You should also be able to check
https://github.com/MIT-DB-Class/hw-answers-(your student name)/tree/lab2
Git is a distributed version control system. This means everything operates
offline until you run git pull or git push. This is a great feature.
The bad thing is that you may forget to git push your changes. This is why we
strongly, strongly suggest that you check GitHub to be sure that what you
want us to see matches up with what you expect.
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 6.830-staff@mit.edu. When you do, please try to include:
-
A description of the bug.
-
A .java file we can drop in the
test/simpledbdirectory, 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 Piazza if you feel you have run into a bug.
50% 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 pull your repo, replace the files mentioned above, compile it, and then grade it. It will look roughly like this:
[replace build.xml, HeapFileEncoder.java, and test]
$ git checkout -- build.xml src/java/simpledb/HeapFileEncoder.java 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 50% 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!