Write sharding in DynamoDB - Step-by-Step Execution

Concept Flow - Write sharding

Start Write Request

↓

Determine Shard Key

↓

Select Shard Table/Partition

↓

Write Data to Selected Shard

↓

Confirm Write Success

↓

End Write Request

Write sharding splits data writes across multiple partitions or tables to spread load and improve performance.

Execution Sample

DynamoDB

function writeData(item) {
  const shardKey = hash(item.userId) % 3;
  const tableName = 'UserDataShard' + shardKey;
  dynamoDB.put({TableName: tableName, Item: item});
}

This code chooses a shard based on userId hash and writes the item to that shard's table.

Execution Table

Step	Input Item userId	Shard Key Calculation	Selected Shard Table	Write Action	Result
1	userId=101	hash(101)%3=2	UserDataShard2	Write item to UserDataShard2	Success
2	userId=205	hash(205)%3=1	UserDataShard1	Write item to UserDataShard1	Success
3	userId=309	hash(309)%3=0	UserDataShard0	Write item to UserDataShard0	Success
4	userId=412	hash(412)%3=1	UserDataShard1	Write item to UserDataShard1	Success
5	userId=523	hash(523)%3=2	UserDataShard2	Write item to UserDataShard2	Success
6	-	-	-	-	All writes completed successfully

💡 All items written to their respective shards; no more writes pending.

Variable Tracker

Variable	Start	After 1	After 2	After 3	After 4	After 5	Final
shardKey	-	2	1	0	1	2	N/A
tableName	-	UserDataShard2	UserDataShard1	UserDataShard0	UserDataShard1	UserDataShard2	N/A

Key Moments - 2 Insights

Why do we use hash(userId) % 3 to select the shard?

Using hash(userId) % 3 evenly distributes writes across 3 shards, preventing overload on a single shard as shown in execution_table rows 1-5.

What happens if we write all data to one shard?

All writes would go to one shard causing slow performance and possible throttling, unlike the balanced writes shown in the execution_table.

Visual Quiz - 3 Questions

Look at the execution_table, what shard table is selected for userId=309?

A UserDataShard1

B UserDataShard2

C UserDataShard0

D UserDataShard3

💡 Hint

Check row 3 in the execution_table under 'Selected Shard Table'

At which step does the shardKey equal 1 for the first time?

A Step 2

B Step 1

C Step 3

D Step 4

💡 Hint

Look at the 'Shard Key Calculation' column in execution_table rows 1-4

If we increase shards to 4, how would the shardKey calculation change?

A hash(userId) * 4

B hash(userId) % 4

C hash(userId) % 3

D hash(userId) + 4

💡 Hint

Shard key uses modulo operation with number of shards as divisor, see code in execution_sample

Concept Snapshot

Write Sharding splits data writes across multiple shards.
Use a shard key (like hash(userId) % number_of_shards) to pick shard.
Write data to selected shard to balance load.
Improves write throughput and reduces bottlenecks.
Each shard is a separate partition or table.

Full Transcript

Write sharding in DynamoDB means splitting write requests across multiple shards or tables. Each write uses a shard key, often a hash of a unique identifier like userId, modulo the number of shards. This calculation decides which shard to write to. The write then goes to that shard's table or partition. This spreads the load evenly, avoiding bottlenecks. The execution table shows how different userIds map to different shards and writes succeed. Variables shardKey and tableName change per write to reflect the shard chosen. Beginners often wonder why modulo is used; it ensures even distribution. Also, writing all data to one shard causes slowdowns, which sharding prevents. The quiz checks understanding of shard selection and shard key calculation. The snapshot summarizes the key points for quick review.