science

Tombstone (data store)

Tombstone (data store) 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 Tombstone (data store) rather than just read about it. In short: A tombstone is a deleted record in a replica of a distributed data store. The tombstone is necessary, as distributed data stores use eventual consistency, where only a subset of nodes where the data is stored must respond before an operation is considered to be successful.

Key takeaways

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

Reference excerpt

A tombstone is a deleted record in a replica of a distributed data store. The tombstone is necessary, as distributed data stores use eventual consistency, where only a subset of nodes where the data is stored must respond before an operation is considered to be successful.

Motivation If information is deleted in an eventually-consistent distributed data store, the "eventual" part of the eventual consistency causes the information to ooze through the node structure, where some nodes may be unavailable at time of deletion. But a feature of eventual consistency causes a problem in case of deletion, as a node that was unavailable at that time will try to "update" the other nodes that no longer have the deleted entry, assuming that they have missed an insert of information. Therefore, instead of deleting the information, the distributed data store creates a (usually temporary) tombstone record, which is not returned in response to requests.

Removal of tombstones In order not to fill the data store with useless information, there is a policy to remove tombstones completely. For this, the system checks the age of the tombstone and removes it after a prescribed time has elapsed. In Apache Cassandra, this elapsed time is set with the GCGraceSeconds parameter and the process is named Compaction. Compaction consumes system resources and also slows down computation capacity.

Consequences Because of the delayed removal, the deleted information will appear as empty, after the content of some columns of a number of records has been deleted. After a compaction, the unused columns will be removed from these records.

References

External links Distributed deletes in Apache Cassandra Archived 2011-05-11 at the Wayback Machine

Worked examples

Example 1 — a first encounter with Tombstone (data store)

Start with the simplest possible case. Write down what Tombstone (data store) 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 Tombstone (data store) 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 Tombstone (data store) 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 Tombstone (data store)

In research: Tombstone (data store) 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 Tombstone (data store) 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: Tombstone (data store) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Database stubs, Distributed data stores, so understanding it makes those chapters shorter.
In everyday life: Look for Tombstone (data store) 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.

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How to study Tombstone (data store) in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Tombstone (data store) 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 Tombstone (data store) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Tombstone (data store) in simple terms?

Why does Tombstone (data store) 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 Tombstone (data store)?

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 Tombstone (data store).