StatusQuo: Making Familiar Abstractions Perform Using Program Analysis StatusQuo: Making Familiar...

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StatusQuo: Making Familiar Abstractions Perform Using Program Analysis

Alvin Cheung Samuel Madden

Armando Solar-Lezama MIT

Owen Arden Andrew C. Myers

Cornell

Developing Database Applications

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Application Server SQL Database

Java Application Logic

SQL Query

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SQL Database

PL/SQL Stored Procedures

SQL Query

Application Server

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SQL Database

SQL Query

Application Server

Language Choice for Application Logic

Application Distribution

Program analysis to the rescue!

StatusQuo

•  Express application logic in ways that programmers are comfortable with

•  Job of compiler & runtime to determine the most efficient implementation

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Two Key Technologies

•  Infer queries from imperative code

•  Migrate computation between servers for optimal performance

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Relational Operations in Imperative Code

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List getUsersWithRoles () { List users = getUsersFromDB(); List roles = getRolesFromDB();

List results = new ArrayList();

for (User u : users) {

for (Role r : roles) {

if (u.roleId == r.id)

results.add(u); }}

return results; }

SELECT * FROM user

SELECT * FROM role

List getUsersWithRoles () {

return executeQuery(

“SELECT u FROM users u, roles r

WHERE u.roleId == r.id

ORDER BY u.roleId, r.id”; }

convert to

Relational Operations in Imperative Code

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List getUsersWithRoles () { List users = getUsersFromDB(); List roles = getRolesFromDB();

List results = new ArrayList();

results.add(u); }}

return results; }

List getUsersWithRoles () {

return executeQuery(

“SELECT u FROM users u, roles r

WHERE u.roleId == r.id

ORDER BY u.roleId, r.id”; }

convert to

Find a variable that we can rewrite into a

SQL expression

post-condition variable results

Query By Synthesis (QBS)

•  Identify potential code fragments –  i.e., regions of code that fetches persistent

data and return values

•  Find SQL expressions for post-condition variables

•  Try to prove that those expressions preserve program semantics –  if so, convert the code!

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Initial Code Fragments Identification

•  Find program points that retrieve

persistent data

•  Run an inter-procedural analysis that: – determine where persistent data are used – delimit code fragment to analyze

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Search for Post-Condition Expressions

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List getUsersWithRoles () { List users = query(select * from users); List roles = query(select * from roles);

List results = [];

results = results : [] }}

return results; }

Relations involved: users, roles Possible expressions to consider for results: σf(users) topf(users) πf(users ⨝g roles) πf(σg(users) ⨝h roles) other expressions involving users, roles

Infinite search space size!

users roles

results

Constraints for Post-Condition Expressions

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List getUsersWithRoles () { List users = query(select * from users); List roles = query(select * from roles);

List results = [];

results = results : [] }}

return results; }

users roles

results

Hoare-style program verification

post-condition expression

outer loop invariant

outer loop invariant outer loop terminates

then post-condition expression

is true and

is true

Still need a smarter way to search

results = πuser( users ⨝roleId = id roles )

results = πuser( users[0 .. i] ⨝roleId = id roles )

Search for Post-Condition Expressions and Invariants

•  Use program synthesis as search engine

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Program synthesizer

Symbolic desc. of search space

Solution constraints

Expression that satisfies all the constraints

Symbolic manipulation

Counter-example driven search

Experiments

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Real-world Evaluation

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Wilos (project management application) – 62k LOC

Operation type # Fragments found

# Fragments converted

Projection 1 1

Selection 13 10

Join 7 7

Aggregation 11 10

Total 33 28

0 20K 40K 60K 80K 100K

Number of roles / users in DB

original (lazy)

inferred (lazy)

Performance Evaluation: Join Query

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Nested-loop join Hash join! O(n2) O(n)

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SQL Database

SQL Query

Application Server

Application Distribution

Running Example

discount = executeQuery("select discount from customers where id = " + cid);

totalAmount = orderTotal * (1 – discount);

credit = executeQuery("select credit from customers where id = " + cid);

if (credit < totalAmount)

printToConsole("Only " + credit + " in account!");

executeUpdate("update customer set credit = " + (credit – totalAmount) + " where id = " + cid);

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Actual Execution

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Actual Execution

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network communication

Speeding up Execution

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data dependency DB

control dependency

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DB Server

control dependency

data dependency

Introducing Pyxis

•  “Store-procedurizes” DB apps and pushes computation to the DB

•  Adaptively controls the amount of computation pushed to DB for optimal performance

•  No programmer intervention required

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Using Pyxis

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How Pyxis Works

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Instrument

Partition

Monitor

App Server DB Server

Deploy

Java SQL Java SQL Java

SQL Java SQL

SQL Java

Java SQL Java SQL Java SQL Java

control transfer

How Pyxis Works

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Monitor

App Server DB Server

Deploy Java

SQL Java

control transfer

Instrument

Partition

Java SQL Java SQL Java SQL Java

Generating Program Partitions

•  Deploy and profile application as-is •  Construct a dependence graph of

program statements – captures both control and data flow

•  Formulate linear program from profile data and dependence graph – solution gives a partitioning of the source

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Executing Partitioned Programs

•  Pyxis compiler translates partitioned code into standard Java code

•  Pyxis runtime executes compiled Java code – runtime is just another Java program

running on a standard JVM –  includes monitoring component to

determine partition switching

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Experiments

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Experiment Setup

•  TPC-C Java implementation – 20 terminals issuing new order transactions – DB server has 16 cores total

– Compared against two implementations:

•  JDBC: everything on app server except for JDBC stmts •  Manual: custom “store procedurized”

implementation where everything is on the DB server

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100 300 500 700 900 1100 1300

Average Thruput (xact / s)

Manual

All Cores Available

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Pyxis generated implementation: 3x latency reduction 1.7x thruput increase

StatusQuo

Ease DB application development

Convert imperative program statements into declarative SQL

Fully automatic code partitioning using

application and server characteristics

db.csail.mit.edu/statusquo

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StatusQuo: Making Familiar Abstractions Perform Using Program Analysis StatusQuo: Making Familiar...

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