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DynamoDB DVA

Links: 102 AWS DVA Index

Partition keys

  • Also known as primary key.
  • Option 1: Partition Key (HASH)

    • Partition key must be unique for each item
    • Partition key must be diverse so that the data is distributed
    • Example: User_ID for a users table
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  • Option 2: Partition Key + Sort Key (HASH + RANGE)

    • The combination must be unique for each item
    • Data is grouped by partition key
    • Example: users-games table, User_ID for Partition Key and Game_ID for Sort Key
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What is the best Partition Key to maximise data distribution? movie_id ,producer_name, leader_actor_name, movie_language?
  • movie_id has the highest cardinality so it's a good candidate movie_language doesn't take many values and may be skewed towards English so it's not a great choice for the Partition Key


  • Use a SQL-like syntax to manipulate DynamoDB tables
  • Supports some (but not all) statements:
  • It supports Batch operations

Optimistic Locking

  • DynamoDB has a feature called Conditional Writes
  • It is type of concurrency model.
  • A strategy to ensure an item hasn't changed before you update/delete it
  • Each item has an attribute that acts as a version number
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DynamoDB Streams

  • DynamoDB Streams
  • Architectures possible using DynamoDB streams:
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  • Ability to choose the information that will be written to the stream:
    • KEYS_ONLY: only the key attributes of the modified item
    • NEW_IMAGE: the entire item, as it appears after it was modified
    • OLD_IMAGE: the entire item, as it appeared before it was modified
    • NEW_AND_OLD_IMAGES: both the new and the old images of the item
  • DynamoDB Streams are made of shards, just like Kinesis Data Streams. This is the reason why KCL works with DynamoDB.
    • You don't provision shards, this is automated by AWS
Records are not retroactively populated in a stream after enabling it

DynamoDB Streams & Lambda

  • You need to define an Event Source Mapping to read from a DynamoDB Streams
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  • You need to ensure the Lambda function has the appropriate permissions
  • Lambda function is invoked synchronously

DynamoDB TTL

  • It is possible to delete items in DynamoDB after a certain time automatically.
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  • Doesn't consume any WCUs (i.e., no extra cost)
  • The TTL attribute must be a Number data type with Unix Epoch timestamp value
  • Expired items deleted within 48 hours of expiration time.
  • Expired items, that haven't been deleted, appears in reads/queries/scans (if you don't want them, filter them out)
  • Expired items are deleted from both LSIs and GSIs
  • A delete operation for each expired item enters the DynamoDB Streams (can help recover expired items)
  • Use case:
    • deleting expired cookies of users and then prompting them to login again.
    • reduce stored data by keeping only current items
    • adhere to regulatory obligations

DynamoDB CLI

  • --projection-expression: one or more attributes to retrieve. Retrieve a subset of attributes.
  • --filter-expression: filter items before returned to you. Filter happens on the client side.
    • If we want the filtering to happen on server side we use a query.
  • General AWS CLI Pagination options (e.g., DynamoDB, S3, ...)
    • --page-size: specify that AWS CLI retrieves the full list of items but with a larger number of API calls instead of one API call (default: 1000 items)
      • So suppose if there are 100 items in the table and you set --page-size to 25 then 4 API calls will be made to fetch the data.
    • --max-items: max number of items to fetch (returns NextToken)
      • If you want to retrieve only 25 items from a table of 100 items we use --max-items.
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    • --starting-token: specify the last NextToken to retrieve the next set of items
      • Once we have the NextToken we use it as an argument to --starting-token along with --max-items
      • If we don't have any next token then this means we are at the end.
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DynamoDB Transactions

  • Coordinated, all-or-nothing operations (add/update/delete) to multiple items across one or more tables.
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  • Provides Atomicity, Consistency, Isolation, and Durability (ACID)
  • Read Modes: Eventual Consistency, Strong Consistency, Transactional
  • Write Modes: Standard, Transactional
  • Consumes 2x WCUs & RCUs
    • Since DynamoDB performs 2 operations for every item (prepare & commit)
  • The two operations performed by DynamoDB are:
    • TransactGetItems: one or more GetItem operations
    • TransactWriteItems: one or more PutItem, UpdateItem, and DeleteItem operations
  • Use cases: financial transactions, managing orders, multiplayer games
  • Capacity Computations:
    • 3 Transactional writes per second, with item size 5 KB: 3*5*2 = 30WCUs
    • 5 Transaction reads per second with item size 5 KB: 5*(8/4)*2 = 20WCUs

DynamoDB as Session State Cache

  • It's common to use DynamoDB to store session state
DynamoDB vs ElastiCache for session state
  • If the question asks for in-memory solution then use ElastiCache
  • If the question asks for serverless/auto-scaling solution then go for DynamoDB

DynamoDB Write Sharding

  • Imagine we have a voting application with two candidates, candidate A and candidate B
  • If Partition Key is Candidate_ID, this results into two partitions, which will generate issues (e.g., Hot Partition)
  • A strategy that allows better distribution of items evenly across partitions
  • Add a suffix to Partition Key value
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  • Two methods:
    • Shading Using Random Suffix
    • Shading Using Calculated Suffix

DynamoDB Write Types

  • There are 4 types of writes:
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DynamoDB with S3

  • Storing large objects:
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  • Indexing S3 objects metadata:
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DynamoDB Operations

  • Table Cleanup:
    • Option 1: Scan + DeleteItem
      • Very slow, consumes RCU & WCU, expensive
    • Option 2: Drop Table + Recreate table
      • Fast, efficient, cheap
  • Copying a DynamoDB Table
    • Option 1: Using AWS Data Pipeline
      • Uses an EMR cluster and S3 behind the scenes
    • Option 2: Backup and restore into a new table
      • Takes some time
    • Option 3: Scan + PutItem or BatchWriteItem
      • Write your own code

Miscellaneous Features

  • Encryption at rest using AWS KMS and in-transit using SSL/TLS
  • For backup and restore we have Point-in-time Recovery (PITR) just like RDS
  • For migrating data to and from DynamoDB we use DMS.
  • Fine grained access control for users:
    • Using Web Identity Federation or Cognito Identity Pools, each user gets AWS credentials
    • You can assign an lAM Role to these users with a Condition to limit their API access to DynamoDB
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    • LeadingKeys limit row-level access for users on the Primary Key

Last updated: 2022-06-08