What is a DynamoDB?

Scalable

Fast, Predictable Performance

Easy Administration

Built-in Fault Tolerance

Flexible

Efficient Indexing

Cost Effective

Integrated Monitoring

Is a Key - Value storage

with document support

DynamoDB Data Model Concept

Table

Data Model Concept

Item

Table

Data Model Concept

Item

Attribute

DynamoDB is schema-less

each attribute defines it

max size 400kB

Data Model Concept

Attribute

Hash key

Hash keys:

mandatory for all items in table
defines data partitioning
represents key-value pattern

Data Model Concept

Attribute

Hash key

Range keys:

With them 1:N relation is possible
Enables rich queries like ==, <, >, begins, etc.
Together with hash key creates primary key composition

Range key

Indexes

Local Secondary Index (LSI)
Global Secondary Index (GSI)

Data Model Concept

Attribute

Hash key

Local secondary index:

Alternative range key with same hash
Total size of ale LSI cannot extend 10 GB
Query will fetch automatically all attributes from table
Read & write capacity consumed from a table

Range key

Data Model Concept

Attribute

Hash key

Global secondary index:

New hash and/or range key
No size limit
Query over a table across all partitions
Query can only request projected attributes

Range key

DynamoDB data types

Scalar

Number
String
Binary
Boolean
Null

Multi-value

String set
Number set
Binary set

Document

list
map

{
    "day": "Monday",
    "unreadEmails": 42,
    "dayPhoto" : "dGhpcyB0ZXh0IGlzIGJhc2U2NC1lbmNvZGVk",
    "itemsOnMyDesk": [
        "coffee Cup",
        "telephone",
        {
            "pens": { "Quantity" : 3},
            "pencils": { "Quantity" : 2},
            "erasers": { "Quantity" : 1}
        }
    ]
}

Provisioning

===

Throughput

Read capacity

One strongly consistency read for items up to 4KB
For eventual consistency up to 8KB
How to:
Number of items read x 4KB

Write capcity

One write per second for item up to 1KB

How to:

Number of items per write x 1KB

Example

498 * 20 bytes / 1024 bytes / 4kB ~ 2,43 = 3 Read capacity units

498 * 20 bytes / 1024 bytes / 1kB ~ 9,73 = 10 Write capacity units

Partitioning

Partition 1

Partition 2

Partition N

Table

DynamoDB automatically partition data using hash key

How to count/predict partitioning

considering size only

considering table read/write throughput

tableSizeInBytes / 10GB

readCapacity / 3000 + writeCapacity / 1000

Example

1) RCU: 2000 and WCU: 1000

2000 / 3000 + 1000 / 1000 = 1.(3) ==> 2 partitions

2) Table size = 1TB

1000 GB / 10 GB = 10 partitions,

then throughput based on example 1:

200 RCU and 100 WCU per partition

Example

How hash key may interfere

Development

How to?

Many SDK provided by AWS!

Java
Java script
.Net
Python
Ruby
iOS
Android

Table creation

There are 2 possibilities to create a DynamoDB table

via AWS Web console

via API

DynamoDB dynamoDB = new DynamoDB(new AmazonDynamoDBClient(
	new ProfileCredentialsProvider()));

CreateTableRequest request = new CreateTableRequest()
		.withTableName(tableName)
		.withKeySchema(keySchema)
		.withAttributeDefinitions(attributeDefinitions)
		.withProvisionedThroughput(new ProvisionedThroughput()
		    .withReadCapacityUnits(5L)
			.withWriteCapacityUnits(6L));

Table table = dynamoDB.createTable(request);

Demo

Table API

createTable
describeTable
updateTable
deleteTable
listTables
waitFor

Current API calls

Item API

putItem
updateItem
deleteItem
getItem
batchGetItem
batchWriteItem
query
scan

Demo

Transactions

ACID in DynamoDB world

Available via external lib https://github.com/awslabs/dynamodb-transactions
Atomicity is being performed with 2 additional tables
- TxRecords
  Store information about transaction: status, items, updateCommands
- TxImages
  Store information about item before transaction and a ref to TxRecord
Isolation:
- Read and ignore lock, ignore pending transactions (weakest)
- Read only commited items, ignore locks
- Use read locks the same as implementing transactions

DynamoDB

What is a DynamoDB?

Scalable

Fast, Predictable Performance

Easy Administration

Built-in Fault Tolerance

Flexible

Efficient Indexing

Cost Effective

Integrated Monitoring

Is a Key - Value storage

with document support

DynamoDB Data Model Concept

Indexes

DynamoDB data types

Scalar

Multi-value

Document

Provisioning

===

Throughput

Read capacity

Write capcity

Example

Partitioning

How to count/predict partitioning

Example

Example

Development

How to?

Many SDK provided by AWS!

Table creation

Demo

Table API

Current API calls

Item API

Demo

Transactions

Some conclusion

Maybe?

Q & A

Links

Thanks!