![I N D E X I N G J S O N D O C U M E N T S
{
"locations": [
{
"country": "Germany",
"city": "Berlin"
},
{
"country": "France",
"city": "Paris"
}
],
"headquarter": "Belgium",
"exports": [
{ "city": "Moscow" },
{ "city": "Athens" }
]
}
locations headquarter exports
0
country city
Germany Berlin
1
country city
France Paris
0 1
city
Athens
city
Moscow
Belgium](https://image.slidesharecdn.com/brk3319-180508194355/85/Technical-overview-of-Azure-Cosmos-DB-44-320.jpg)
![I N D E X I N G J S O N D O C U M E N T S
{
"locations": [
{
"country": "Germany",
"city": "Bonn",
"revenue": 200
}
],
"headquarter": "Italy",
"exports": [
{
"city": "Berlin",
"dealers": [
{ "name": "Hans" }
]
},
{ "city": "Athens" }
]
}
locations headquarter exports
0
country city
Germany Bonn
revenue
200
0 1
citycity
Berlin
Italy
dealers
0
name
Hans](https://image.slidesharecdn.com/brk3319-180508194355/85/Technical-overview-of-Azure-Cosmos-DB-45-320.jpg)
![I N D E X P O L I C I E S
CUSTOM INDEXING POLICIES
Though all Azure Cosmos DB data is indexed by default, you
can specify a custom indexing policy for your collections.
Custom indexing policies allow you to design and customize
the shape of your index while maintaining schema flexibility.
• Define trade-offs between storage, write and query
performance, and query consistency
• Include or exclude documents and paths to and from the
index
• Configure various index types
{
"automatic": true,
"indexingMode": "Consistent",
"includedPaths": [{
"path": "/*",
"indexes": [{
"kind": "Hash",
"dataType": "String",
"precision": -1
}, {
"kind": "Range",
"dataType": "Number",
"precision": -1
}, {
"kind": "Spatial",
"dataType": "Point"
}]
}],
"excludedPaths": [{
"path": "/nonIndexedContent/*"
}]
}](https://image.slidesharecdn.com/brk3319-180508194355/85/Technical-overview-of-Azure-Cosmos-DB-48-320.jpg)
Technical overview of Azure Cosmos DB
- 3. I N T H I S S E S S I O N … Azure Cosmos DB Core Concepts and What’s New @ //Build/ 2018 TL;DR High-Level Overview Resource Model Request Units Partitioning Replication Automatic Indexing New Goodies Q&A
- 5. SQL MongoDB Table API Turnkey global distribution Elastic scale out of storage & throughput Guaranteed low latency at the 99th percentile Comprehensive SLAs Five well-defined consistency models A Z U R E C O S M O S D B DocumentColumn-family Key-value Graph A globally distributed, massively scalable, multi-model database service
- 7. Leveraging Azure Cosmos DB to automatically scale your data across the globe This module will reference partitioning in the context of all Azure Cosmos DB modules and APIs. R E S O U R C E M O D E L Account DatabaseDatabaseDatabase DatabaseDatabaseContainer DatabaseDatabaseItem
- 8. Account DatabaseDatabaseDatabase DatabaseDatabaseContainer DatabaseDatabaseItem A C C O U N T U R I A N D C R E D E N T I A L S ********.azure.com IGeAvVUp …
- 9. C R E AT I N G A C C O U N T Account DatabaseDatabaseDatabase DatabaseDatabaseContainer DatabaseDatabaseItem
- 10. D ATA B A S E R E P R E S E N TAT I O N S Account DatabaseDatabaseDatabase DatabaseDatabaseContainer DatabaseDatabaseItem DatabaseDatabaseContainer DatabaseDatabaseItem
- 11. C O N TA I N E R R E P R E S E N TAT I O N S Account DatabaseDatabaseDatabase DatabaseDatabaseContainer DatabaseDatabaseItem = Collection Graph Table
- 12. C R E AT I N G C O L L E C T I O N S – S Q L A P I Account DatabaseDatabaseDatabase DatabaseDatabaseContainer DatabaseDatabaseItem
- 13. C O N TA I N E R - L E V E L R E S O U R C E S Account DatabaseDatabaseDatabase DatabaseDatabaseContainer DatabaseDatabaseItem ConflictSproc Trigger UDF
- 14. S Y S T E M TO P O LO G Y ( B E H I N D T H E S C E N E S ) Resource Manager Language Runtime(s) Hosts Query Processor RSM Index Manager Bw-tree++/ LLAMA++ Log Manager IO Manager Resource Governor Transport Database engine Admission control … … Planet Earth Azure regions Datacenters Stamps Fault domains Cluster Machine Replica Database engine Container Various agents
- 15. R E S O U R C E H I E R A R C H Y CONTAINERS Logical resources “surfaced” to APIs as tables, collections or graphs, which are made up of one or more physical partitions or servers. RESOURCE PARTITIONS • Consistent, highly available, and resource-governed coordination primitives • Consist of replica sets, with each replica hosting an instance of the database engine Containers Resource Partitions CollectionsTables Graphs Tenants Leader Follower Follower Forwarder Replica Set To remote resource partition(s)
- 17. R E Q U E S T U N I T S Request Units (RUs) is a rate-based currency Abstracts physical resources for performing requests Key to multi-tenancy, SLAs, and COGS efficiency Foreground and background activities % IOPS% CPU% Memory
- 18. R E Q U E S T U N I T S Normalized across various access methods 1 read of 1 KB document from a single partition Each request consumes fixed RUs Applies to reads, writes, query, and stored procedures GET POST PUT Query … = = = =
- 19. R E Q U E S T U N I T S Provisioned in terms of RU/sec Rate limiting based on amount of throughput provisioned Can be increased or decreased instantaneously Metered Hourly Background processes like TTL expiration, index transformations scheduled when quiescent Min RU/sec Max RU/sec IncomingRequests Replica Quiescent Rate limit No rate limiting
- 20. * N E W * P R O V I S I O N R U / S F O R A S E T O F C O N TA I N E R S Remove friction for OSS NoSQL APIs Provision RU/sec shared across containers Mix containers with dedicated throughput and containers with shared throughput Elastically scale provisioned throughput for a set of containers at any time
- 22. E L A S T I C S C A L E O U T O F S TO R A G E A N D T H R O U G H P U T SCALES AS YOUR APPS’ NEEDS CHANGE Database elastically scales storage and throughput How? Scale-out! Collections can span across large clusters of machines Can start small and seamlessly grow as your app grows
- 23. E L A S T I C S C A L E O U T O F S TO R A G E A N D T H R O U G H P U T SCALES AS YOUR APPS’ NEEDS CHANGE Database elastically scales storage and throughput How? Scale-out! Collections can span across large clusters of machines Can start small and seamlessly grow as your app grows
- 24. PA R T I T I O N S Cosmos DB Container (e.g. Collection) Partition Key: User ID Logical Partitioning Abstraction Behind the Scenes: Physical Partition Sets hash(User ID) Psuedo-random distribution of data over range of possible hashed values
- 25. PA R T I T I O N S … Partition 1 Partition 2 Partition n Frugal # of Partitions based on actual storage and throughput needs (yielding scalability with low total cost of ownership) hash(User ID) Pseudo-random distribution of data over range of possible hashed values Andrew Mike … Bob Dharma Shireesh Karthik Rimma Alice Carol …
- 26. PA R T I T I O N S … Partition 1 Partition 2 Partition n What happens when partitions need to grow? hash(User ID) Pseudo-random distribution of data over range of possible hashed values Andrew Mike … Bob Dharma Shireesh Karthik Rimma Alice Carol …
- 27. PA R T I T I O N S Partition Ranges can be dynamically sub-divided to seamlessly grow database as the application grows while simultaneously maintaining high availability. Partition management is fully managed by Azure Cosmos DB, so you don't have to write code or manage your partitions. + Partition x Partition x1 Partition x2 hash(User ID) Pseudo-random distribution of data over range of possible hashed values Rimma Karthik … Dharma Shireesh Karthik Rimma Alice Carol … Dharma Shireesh …
- 28. PA R T I T I O N S Best Practices: Design Goals for Choosing a Good Partition Key • Distribute the overall request + storage volume • Avoid “hot” partition keys Steps for Success • Ballpark scale needs (size/throughput) • Understand the workload • # of reads/sec vs writes per sec • Use pareto principal (80/20 rule) to help optimize bulk of workload • For reads – understand top 3-5 queries (look for common filters) • For writes – understand transactional needs General Tips • Build a POC to strengthen your understanding of the workload and iterate (avoid analyses paralysis) • Don’t be afraid of having too many partition keys • Partitions keys are logical • More partition keys more scalability • Partition Key is scope for multi-record transactions and routing queries • Queries can be intelligently routed via partition key • Omitting partition key on query requires fan-out
- 29. * N E W * B U L K E X E C U TO R L I B R A R Y Easy out-of-the-box bulk operation functionality Supports bulk import and update Auto handles congestion control + transient errors 10x client-side performance improvement Easily scale-out clients across more VMs Available starting with .NET and Java
- 32. T U R N K E Y G LO B A L D I S T R I B U T I O N High Availability • Automatic and Manual Failover • Multi-homing API removes need for app redeployment Low Latency (anywhere in the world) • Packets cannot move fast than the speed of light • Sending a packet across the world under ideal network conditions takes 100’s of milliseconds • You can cheat the speed of light – using data locality • CDN’s solved this for static content • Azure Cosmos DB solves this for dynamic content
- 33. T U R N K E Y G LO B A L D I S T R I B U T I O N • Automatic and transparent replication worldwide • Each partition hosts a replica set per region • Customers can test end to end application availability by programmatically simulating failovers • All regions are hidden behind a single global URI with multi-homing capabilities • Customers can dynamically add / remove additional regions at any time Writes/ Reads Reads "airport" : “AMS" "airport" : “MEL" West US Container "airport" : "LAX" Local Distribution (via horizontal partitioning) GlobalDistribution(ofresourcepartitions) Reads 30K transactions/sec Writes/ Reads Reads Reads West Europe 30K transactions/sec Partition-key = "airport"
- 34. R E P L I C AT I N G D ATA G LO B A L LY
- 35. R E P L I C AT I N G D ATA G LO B A L LY
- 36. R E P L I C AT I N G D ATA G LO B A L LY
- 37. A U TO M AT I C FA I LO V E R
- 38. A U TO M AT I C FA I LO V E R
- 39. M A N U A L FA I LO V E R
- 40. Strong Bounded-staleness Session Consistent prefix Eventual F I V E W E L L - D E F I N E D C O N S I S T E N C Y M O D E L S CHOOSE THE BEST CONSISTENCY MODEL FOR YOUR APP Five well-defined, consistency models Overridable on a per-request basis Provides control over performance-consistency tradeoffs, backed by comprehensive SLAs. An intuitive programming model offering low latency and high availability for your planet-scale app. CLEAR TRADEOFFS • Latency • Availability • Throughput
- 41. * N E W * M U LT I - M A S T E R ( P R E V I E W ) Perfect for Intelligent Cloud and Intelligent Edge Applications Write scalability around the world Low latency writes around the world 99.999% High Availability around the world Well-defined consistency models Comprehensive conflict management
- 43. H A N D L E A N Y D ATA W I T H N O S C H E M A O R I N D E X I N G R E Q U I R E D Azure Cosmos DB’s schema-less service automatically indexes all your data, regardless of the data model, to delivery blazing fast queries. Item Color Microwave safe Liquid capacity CPU Memory Storage Geek mug Graphite Yes 16ox ??? ??? ??? Coffee Bean mug Tan No 12oz ??? ??? ??? Surface book Gray ??? ??? 3.4 GHz Intel Skylake Core i7- 6600U 16GB 1 TB SSD • Automatic index management • Synchronous auto-indexing • No schemas or secondary indices needed • Works across every data model GEEK
- 44. I N D E X I N G J S O N D O C U M E N T S { "locations": [ { "country": "Germany", "city": "Berlin" }, { "country": "France", "city": "Paris" } ], "headquarter": "Belgium", "exports": [ { "city": "Moscow" }, { "city": "Athens" } ] } locations headquarter exports 0 country city Germany Berlin 1 country city France Paris 0 1 city Athens city Moscow Belgium
- 45. I N D E X I N G J S O N D O C U M E N T S { "locations": [ { "country": "Germany", "city": "Bonn", "revenue": 200 } ], "headquarter": "Italy", "exports": [ { "city": "Berlin", "dealers": [ { "name": "Hans" } ] }, { "city": "Athens" } ] } locations headquarter exports 0 country city Germany Bonn revenue 200 0 1 citycity Berlin Italy dealers 0 name Hans
- 46. I N D E X I N G J S O N D O C U M E N T S Athens locations headquarter exports 0 country city Germany Bonn revenue 200 0 1 citycity Berlin Italy dealers 0 name Hans locations headquarter exports 0 country city Germany Berlin 1 country city France Paris 0 1 city Athens city Moscow Belgium
- 47. I N V E R T E D I N D E X locations headquarter exports 0 country city Germany Berlin revenue 200 0 1 city Athens city Berlin Italy dealers 0 name Hans Bonn 1 country city France Paris Belgium Moscow
- 48. I N D E X P O L I C I E S CUSTOM INDEXING POLICIES Though all Azure Cosmos DB data is indexed by default, you can specify a custom indexing policy for your collections. Custom indexing policies allow you to design and customize the shape of your index while maintaining schema flexibility. • Define trade-offs between storage, write and query performance, and query consistency • Include or exclude documents and paths to and from the index • Configure various index types { "automatic": true, "indexingMode": "Consistent", "includedPaths": [{ "path": "/*", "indexes": [{ "kind": "Hash", "dataType": "String", "precision": -1 }, { "kind": "Range", "dataType": "Number", "precision": -1 }, { "kind": "Spatial", "dataType": "Point" }] }], "excludedPaths": [{ "path": "/nonIndexedContent/*" }] }
- 50. P R O V I S I O N T H R O U G H P U T F O R A S E T O F C O N TA I N E R S Remove friction for OSS NoSQL APIs Provision RU/sec shared across containers Mix containers with dedicated throughput and containers with shared throughput Elastically scale provisioned throughput for a set of containers at any time
- 51. B U L K E X E C U TO R L I B R A R Y Easy out-of-the-box bulk operation functionality Supports bulk import and update Auto handles congestion control + transient errors 10x client-side performance improvement Easily scale-out clients across more VMs Available starting with .NET and Java
- 52. M U LT I - M A S T E R @ G LO B A L S C A L E ( P R E V I E W ) Perfect for Intelligent Cloud and Intelligent Edge Applications Write scalability around the world Low latency writes around the world 99.999% High Availability around the world Well-defined consistency models Comprehensive conflict management
- 53. V N E T S E R V I C E E N D P O I N T Secure communication without exposing public endpoints Limit access to specific VNET(s) subnet(s) Compatible with IP Firewall ACLs Available in all Azure regions
- 54. J AVA A S Y N C L I B R A R Y F O R S Q L A P I New Async API surface for event-based programs w/ observable sequencies Leverages popular RxJava library 2x client-side performance improvement Improved user experience
- 55. R E C A P Azure Cosmos DB Core Concepts and What’s New @ //Build/ 2018 TL;DR High-Level Overview Resource Model Request Units Partitioning Replication Automatic Indexing New Goodies Q&A