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MongoDBquery~5 mins

Hash-based sharding in MongoDB

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Introduction

Hash-based sharding helps split data evenly across many servers. It makes sure no single server gets too much work.

When you have a large collection that needs to be split across multiple servers.
When you want to balance the load evenly without worrying about data order.
When your queries mostly use the shard key for fast lookups.
When you want to avoid hotspots caused by sequential data inserts.
When you want to scale your database horizontally by adding more servers.
Syntax
MongoDB
sh.shardCollection("database.collection", { "shardKeyField": "hashed" })
The shard key field must be indexed and present in all documents.
Hashing the shard key spreads data randomly but evenly across shards.
Examples
This command shards the orders collection in the shop database using a hashed orderId field.
MongoDB
sh.shardCollection("shop.orders", { "orderId": "hashed" })
This shards the profiles collection by hashing the userId field to distribute user data evenly.
MongoDB
sh.shardCollection("users.profiles", { "userId": "hashed" })
Sample Program

This example enables sharding on the shop database and shards the orders collection using a hashed orderId field.

MongoDB
use admin
sh.enableSharding("shop")
sh.shardCollection("shop.orders", { "orderId": "hashed" })
OutputSuccess
Important Notes

Hash-based sharding works best when your shard key has high cardinality (many unique values).

It is not good for range queries because hashed keys do not preserve order.

Once you shard a collection, changing the shard key is difficult.

Summary

Hash-based sharding splits data evenly by hashing the shard key.

It helps balance load and avoid hotspots.

Use it when you want even data distribution without caring about order.

Practice

(1/5)
1.

What is the main purpose of hash-based sharding in MongoDB?

easy
A. To store data in sorted order on each shard
B. To compress data before storing it
C. To replicate data for backup purposes
D. To evenly distribute data across shards using a hash function

Solution

  1. Step 1: Understand hash-based sharding concept

    Hash-based sharding uses a hash function on the shard key to distribute data evenly.
  2. Step 2: Compare options with concept

    Only To evenly distribute data across shards using a hash function describes even distribution using hashing, which matches the concept.
  3. Final Answer:

    To evenly distribute data across shards using a hash function -> Option D
  4. Quick Check:

    Hash-based sharding = even data distribution [OK]
Hint: Hash-based sharding means even spread by hashing key [OK]
Common Mistakes:
  • Confusing hash-based with range-based sharding
  • Thinking it sorts data on shards
  • Mixing sharding with replication
2.

Which of the following is the correct way to create a hashed shard key on the field userId in MongoDB?

sh.shardCollection("mydb.users", { ??? })
easy
A. { userId: 1 }
B. { userId: "hashed" }
C. { userId: -1 }
D. { userId: true }

Solution

  1. Step 1: Recall syntax for hashed shard key

    MongoDB requires the shard key field to be set to "hashed" as a string to enable hash-based sharding.
  2. Step 2: Match options with syntax

    Only { userId: "hashed" } uses the correct syntax: { userId: "hashed" }.
  3. Final Answer:

    { userId: "hashed" } -> Option B
  4. Quick Check:

    Hashed shard key syntax = { field: "hashed" } [OK]
Hint: Hashed keys use string "hashed" in shard key spec [OK]
Common Mistakes:
  • Using 1 or -1 instead of "hashed"
  • Using boolean true instead of string
  • Omitting quotes around hashed
3.

Given a collection sharded by { userId: "hashed" }, which shard will store the document { userId: 42, name: "Alice" }?

Assume the hash function maps 42 to a hash value that falls into shard 2's range.

medium
A. Shard 2
B. Cannot determine without full hash map
C. Shard 3
D. Shard 1

Solution

  1. Step 1: Understand hashed shard key routing

    Documents are routed to shards based on the hash of the shard key value.
  2. Step 2: Use given hash mapping

    The problem states the hash of 42 falls into shard 2's range, so the document goes to shard 2.
  3. Final Answer:

    Shard 2 -> Option A
  4. Quick Check:

    Hash value maps to shard 2 [OK]
Hint: Hash value decides shard, not raw key [OK]
Common Mistakes:
  • Assuming shard based on userId value directly
  • Choosing 'Cannot determine' when info is given
  • Confusing shard ranges with key values
4.

Consider this command to shard a collection:

sh.shardCollection("mydb.orders", "orderId: hashed")

After running this, you get an error: "Error: shard key must be an object". What is the likely cause?

medium
A. The shard key argument must be an object, but a string was passed
B. The shard key value should be 1 or -1, not "hashed"
C. The command syntax is correct; the error is from elsewhere
D. The database name is missing in the command

Solution

  1. Step 1: Check shardCollection syntax

    The shard key must be an object specifying the field and type, e.g., { orderId: "hashed" }.
  2. Step 2: Identify error cause

    The error says shard key must be an object, so likely the argument passed was not an object but a string or other type.
  3. Final Answer:

    The shard key argument must be an object, but a string was passed -> Option A
  4. Quick Check:

    Shard key must be an object [OK]
Hint: Shard key must be an object, not a string [OK]
Common Mistakes:
  • Passing shard key as string instead of object
  • Confusing shard key with database name
  • Ignoring error message details
5.

You want to shard a collection by email using hash-based sharding. However, you notice some shards have much more data than others. What could be a reason for this uneven distribution?

hard
A. The shard key was set to { email: 1 } instead of hashed
B. Hash-based sharding always causes uneven data distribution
C. The email field has many duplicate values causing hash collisions
D. The collection is too small to distribute evenly

Solution

  1. Step 1: Understand hash-based sharding behavior

    Hash-based sharding usually distributes data evenly unless many documents share the same shard key value.
  2. Step 2: Analyze cause of uneven data

    If many documents have the same email, their hash is the same, so they go to the same shard, causing imbalance.
  3. Final Answer:

    The email field has many duplicate values causing hash collisions -> Option C
  4. Quick Check:

    Duplicate keys cause uneven shard data [OK]
Hint: Duplicates in shard key cause uneven shard sizes [OK]
Common Mistakes:
  • Assuming hash sharding always balances perfectly
  • Confusing range-based with hash-based sharding
  • Ignoring data distribution of shard key values
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