science

Online aggregation

Online aggregation is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Online aggregation rather than just read about it. In short: Online aggregation is a technique for improving the interactive behavior of database systems processing expensive analytical queries. Almost all database operations are performed in batch mode, i.e. the user issues a query and waits till the database has finished processing the entire query.

Key takeaways

Online aggregation belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Online aggregation to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Online aggregation from memory before moving on to harder problems.

Reference excerpt

Online aggregation is a technique for improving the interactive behavior of database systems processing expensive analytical queries. Almost all database operations are performed in batch mode, i.e. the user issues a query and waits till the database has finished processing the entire query. On the contrary, using online aggregation, the user gets estimates of an aggregate query in an online fashion as soon as the query is issued. For example, if the final answer is 1000, after k seconds, the user gets the estimates in form of a confidence interval like [990, 1020] with 95% probability. This confidence keeps on shrinking as the system gets more and more samples. Online aggregation was proposed in 1997 by Hellerstein, Haas and Wang for group-by aggregation queries over a single table. Later, the authors showed how to evaluate joins in an online fashion. In 2007, Jermaine et al. designed and implemented a prototype database system called Database-Online (or DBO) that computes group-by aggregate query over multiple tables in an online and more importantly in a scalable fashion. All the approaches for online aggregation use random sampling, which is non-trivial in a distributed environment due to inspection paradox of renewal reward theory. In 2011, Pansare et al. proposed a Bayesian model to deal with the inspection paradox and implemented online aggregation for a MapReduce-like environment.

References

Worked examples

Example 1 — a first encounter with Online aggregation

Start with the simplest possible case. Write down what Online aggregation claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Online aggregation before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Online aggregation ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Online aggregation

In research: Online aggregation appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Online aggregation in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Online aggregation is common in secondary-school and first-year university syllabi. It links to neighbouring topics Database stubs, Database theory, so understanding it makes those chapters shorter.
In everyday life: Look for Online aggregation outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Online aggregation in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Online aggregation means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Online aggregation out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Online aggregation in simple terms?

Why does Online aggregation matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Online aggregation?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Online aggregation.