Range-based sharding in MongoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is range-based sharding in MongoDB?

Range-based sharding splits data into chunks based on a range of shard key values. Each shard holds documents within a specific range, like dividing a book by chapters.

beginner

How does MongoDB decide which shard stores a document in range-based sharding?

MongoDB looks at the shard key value of the document and places it in the shard responsible for the range that includes that value.

intermediate

What is a chunk in range-based sharding?

A chunk is a continuous range of shard key values. MongoDB moves chunks between shards to balance data and load.

intermediate

Why might range-based sharding cause hotspots?

If many writes target a small range of shard key values, one shard gets overloaded, causing a hotspot and slowing performance.

beginner

Name one advantage of range-based sharding.

It allows efficient range queries because related data is stored together on the same shard.

In range-based sharding, how is data divided across shards?

A By ranges of shard key values

B Randomly across shards

C By hashing the shard key

D By document size

Range-based sharding divides data by ranges of shard key values, so each shard holds a specific range.

What is a potential problem with range-based sharding?

A Data is evenly distributed

B Chunks cannot move between shards

C Hotspots can form if many writes target one range

D It does not support range queries

Hotspots happen when many writes target a small range, overloading one shard.

What is a chunk in MongoDB range-based sharding?

A A backup copy

B A single document

C A shard server

D A range of shard key values

A chunk is a continuous range of shard key values that MongoDB manages.

Which query type benefits most from range-based sharding?

A Random document lookups

B Range queries on shard key

C Full collection scans

D Queries without shard key

Range queries on the shard key are efficient because related data is stored together.

How does MongoDB balance data in range-based sharding?

A By moving chunks between shards

B By deleting old data

C By copying data to all shards

D By changing shard keys

MongoDB moves chunks between shards to keep data balanced.

Explain how range-based sharding works in MongoDB and why it might cause hotspots.

Think about how dividing data by ranges affects where data goes and how busy shards get.

Describe one advantage and one disadvantage of using range-based sharding.

Consider query speed and load distribution.

Practice

1. What is the main idea behind range-based sharding in MongoDB?

easy

A. Data is randomly distributed across shards.

B. Data is split into ranges based on shard key values.

C. Data is duplicated on all shards for backup.

D. Data is stored only on a single shard.

Solution

1. Step 1: Understand range-based sharding concept

   Range-based sharding divides data into continuous ranges based on shard key values.

2. Step 2: Compare with other options

   Random distribution or duplication are not characteristics of range-based sharding.

3. Final Answer:

   Data is split into ranges based on shard key values. -> Option B

4. Quick Check:

   Range-based sharding = Data split by ranges [OK]

Hint: Remember: range-based means splitting by value ranges [OK]

Common Mistakes:

• Confusing range-based with hash-based sharding
• Thinking data is duplicated on all shards
• Assuming data is randomly distributed

2. Which of the following is the correct way to enable range-based sharding on a collection in MongoDB?

easy

A. sh.shardRangeCollection("db.collection", { "field": 1 })

B. sh.enableRangeSharding("db.collection")

C. db.collection.shardRange({ "field": 1 })

D. sh.shardCollection("db.collection", { "field": 1 })

Solution

1. Step 1: Recall MongoDB sharding command

   The correct command to shard a collection by a key is sh.shardCollection() with the shard key.

2. Step 2: Verify syntax correctness

   sh.shardCollection("db.collection", { "field": 1 }) uses the correct syntax: sh.shardCollection("db.collection", { "field": 1 }). Other options are invalid commands.

3. Final Answer:

   sh.shardCollection("db.collection", { "field": 1 }) -> Option D

4. Quick Check:

   Use sh.shardCollection() to enable sharding [OK]

Hint: Use sh.shardCollection() with shard key object [OK]

Common Mistakes:

• Using non-existent commands like sh.enableRangeSharding
• Incorrect method names like shardRangeCollection
• Passing wrong parameters or missing shard key

3. Given a collection sharded by the field age with ranges: { age: { $lt: 20 } }, { age: { $gte: 20, $lt: 40 } }, and { age: { $gte: 40 } }, which shard will store a document with { age: 35 }?

medium

A. Shard with range { age: { $gte: 20, $lt: 40 } }

B. Shard with range { age: { $lt: 20 } }

C. Shard with range { age: { $gte: 40 } }

D. Document will be stored on all shards

Solution

1. Step 1: Identify the correct range for age 35

   Age 35 fits in the range where age is greater or equal to 20 and less than 40.

2. Step 2: Match the range to the shard

   The shard with range { age: { $gte: 20, $lt: 40 } } will store the document.

3. Final Answer:

   Shard with range { age: { $gte: 20, $lt: 40 } } -> Option A

4. Quick Check:

   35 is between 20 and 40, so goes to that shard [OK]

Hint: Match value to shard range boundaries carefully [OK]

Common Mistakes:

• Choosing the shard with $lt: 20 incorrectly
• Assuming document is stored on all shards
• Confusing range boundaries (gte vs lt)

4. You have a range-based sharded collection on score with ranges: { score: { $lt: 50 } } and { score: { $gte: 50 } }. You try to insert { score: "high" } but get an error. What is the likely cause?

medium

A. The shard key ranges overlap causing conflict.

B. The shard key field is missing in the document.

C. The shard key value type does not match the defined range type.

D. MongoDB does not support string values in shard keys.

Solution

1. Step 1: Understand shard key type requirements

   Shard key values must match the type used in range definitions. Here, ranges expect numeric scores.

2. Step 2: Identify the error cause

   Inserting a string "high" for a numeric shard key causes a type mismatch error.

3. Final Answer:

   The shard key value type does not match the defined range type. -> Option C

4. Quick Check:

   Shard key types must match range types [OK]

Hint: Shard key values must match range data types [OK]

Common Mistakes:

• Assuming missing shard key field causes this error
• Thinking overlapping ranges cause insert errors
• Believing MongoDB disallows strings in shard keys

5. You want to shard a large user collection by signupDate using range-based sharding. Which shard key choice will best support queries filtering users by recent signup dates?

hard

A. Use { signupDate: 1 } as shard key to split by date ranges.

B. Use { userId: 1 } as shard key for even data distribution.

C. Use { signupDate: "hashed" } to hash dates for randomness.

D. Use { lastLogin: 1 } as shard key for login-based queries.

Solution

1. Step 1: Identify query pattern

   Queries filter users by recent signup dates, so shard key should support range queries on signupDate.

2. Step 2: Choose shard key matching query pattern

   Using { signupDate: 1 } enables range-based sharding by date, optimizing these queries.

3. Step 3: Evaluate other options

   Hashing or using unrelated fields won't support efficient range queries on signupDate.

4. Final Answer:

   Use { signupDate: 1 } as shard key to split by date ranges. -> Option A

5. Quick Check:

   Shard key matches query field for best performance [OK]

Hint: Match shard key to common query field for range queries [OK]

Common Mistakes:

• Choosing hashed shard key when range queries are needed
• Picking unrelated fields like userId or lastLogin
• Ignoring query patterns when selecting shard key