MongoDB World 2018: Keynote
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The document discusses MongoDB transactions and concurrency. It provides code examples of how to perform transactions in MongoDB using logical sessions, including inserting a document into a collection and updating related documents in another collection atomically. It also discusses some of the features and timeline for implementing distributed transactions in sharded MongoDB clusters.
![doc = { line_items : [ { item : 5,
quantity : 6 }, … ] }
db.orders.insertOne( doc );
for x in doc.line_items:
db.inventory.update( { _id : x.item },
{ $inc : { number : -1 * x.qty } })](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-3-320.jpg)
![doc = { line_items : [ { item : 5,
quantity : 6 }, … ] }
db.orders.insertOne( doc );
for x in doc.line_items:
db.inventory.update( { _id : x.item },
{ $inc : { number : -1 * x.qty } })](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-4-320.jpg)
![doc = { line_items : [ { item : 5,
quantity : 6 }, … ] }
db.orders.insertOne( doc );
for x in doc.line_items:
db.inventory.update( { _id : x.item },
{ $inc : { number : -1 * x.qty } })](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-5-320.jpg)
![session.start_transaction()
doc = { line_items : [ { item : 5, quantity: 6 }, … ] }
db.orders.insertOne( doc, session=session );
for x in doc.line_items:
db.inventory.update( { _id : x.item } ,
{ $inc : { number : -1 * x.qty } },
session=session )
session.commit_transaction()](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-6-320.jpg)
![{
order_id,
customer_id,
line_iems: [
{
name : ,
price : ,
qty : ,
}
]
}](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-14-320.jpg)
![db.orders.update(
{ order_id : my_order_id },
{ $mul :
{ order_total :
discount,
"line_items.$[].price" :
discount }
}
)
{
order_id,
customer_id,
line_iems: [
{
name : ,
price : ,
qty : ,
}
]
}](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-15-320.jpg)
![Relationships
{
order_id,
line_items: [ … ],
}
{
product_id,
inventory
}
REFERENCE](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-21-320.jpg)
![Relationships
EMBEDDED
{
order_id,
line_items: [
{ product_id,
qty,
subtotal
}
]
}
{
order_id,
line_items: [ … ],
}
{
product_id,
inventory
}
REFERENCE](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-22-320.jpg)
![db.products.find().limit(1).pretty()
{
"_id" : ObjectId("5b116f1b3e1c824cb7950480"),
"id" : "298157062",
"name" : "Uptown Laptop TSA-Friendly Backpack",
"sku" : "MON25232000",
"image" : {
"large" : "/images/products/bags/large_backpack.jpg",
"thumb" : "/images/products/bags/thumb_backpack.jpg"
},
"color" : "black",
"inventory" : 100,
"category" : [
"products",
"bags",
"backpack",
"travel"
],
"price" : NumberDecimal("1233423"),
"reviews" : [ ],
"likes" : 101,
"tweets" : 13,
"type" : "backpack"](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-31-320.jpg)
![grep -o "[0-9]+ms" <filename> |
sort -n |
tail -n 20 |
uniq |
xargs -n 1 -I x grep x <filename>](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-38-320.jpg)
![db.logs.aggregate( [
{ $sort : { time : -1 } },
{ $limit : 20 },
{ $group : { _id : "$queryShape",
count : { $sum : 1 } }
}
] )](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-40-320.jpg)
![# Subscribe to change notifications in a collection.
cursor = client.my_db.my_collection.watch([
{'$match': {'operationType':
{'$in': [
'insert',
'replace' ]
}
}},
{'$match': {'fullDocument.n':
{'$gte': 1}}}
])
# Loops forever.
for change in cursor:
print(change['fullDocument'])](https://image.slidesharecdn.com/mdbw18eliotkeynotesanitized-180716150509/85/MongoDB-World-2018-Keynote-91-320.jpg)
MongoDB World 2018: Keynote
- 1. Eliot Horowitz, CTO & Co-Founder @eliothorowitz
- 3. doc = { line_items : [ { item : 5, quantity : 6 }, … ] } db.orders.insertOne( doc ); for x in doc.line_items: db.inventory.update( { _id : x.item }, { $inc : { number : -1 * x.qty } })
- 4. doc = { line_items : [ { item : 5, quantity : 6 }, … ] } db.orders.insertOne( doc ); for x in doc.line_items: db.inventory.update( { _id : x.item }, { $inc : { number : -1 * x.qty } })
- 5. doc = { line_items : [ { item : 5, quantity : 6 }, … ] } db.orders.insertOne( doc ); for x in doc.line_items: db.inventory.update( { _id : x.item }, { $inc : { number : -1 * x.qty } })
- 6. session.start_transaction() doc = { line_items : [ { item : 5, quantity: 6 }, … ] } db.orders.insertOne( doc, session=session ); for x in doc.line_items: db.inventory.update( { _id : x.item } , { $inc : { number : -1 * x.qty } }, session=session ) session.commit_transaction()
- 9. Marathon to transactions: the homestretch MongoDB 3.0 MongoDB 3.2 MongoDB 3.4 MongoDB 3.6 MongoDB 4.0 Single Replica Set Transactions MongoDB 4.2 Sharded Transactions New Storage engine (WiredTiger) Enhanced replication protocol: stricter consistency & durability Shard membership awareness Consistent secondary reads in sharded clusters Storage support for prepared transactions Transaction – compatible chunk migration WiredTiger default storage engine Logical sessions Make catalog timestamp-aware More extensive Wired Tiger repair Config server manageability improvements Retryable writes Replica set point-in-time reads Transaction manager Read concern "majority" Causal Consistency Recoverable rollback via WT checkpoints Global point-in-time reads Cluster-wide logical clock Recover to a timestamp Oplog applier prepare support for transactions Storage API to changes to use timestamps Sharded catalog improvements Collection catalog versioning Make collection drops two phrase UUIDs in sharding Fast in-place updates to large documents in WT In Progress Done Sharded Transaction Feature
- 12. { order_id, customer_id } { line_item_id, order_id } session.start_transaction() db.line_items.update( { order_id : my_order_id } , { $mul : { price : discout } }, sesison = my_session) db.orders.update( { order_id : my_order_id } , { $mul : { order_total : discount } }, session = my_session ) session.end_transaction()
- 13. { order_id, customer_id } { line_item_id, order_id } session.start_transaction() db.line_items.update( { order_id : my_order_id } , { $mul : { price : discout } }, sesison = my_session) db.orders.update( { order_id : my_order_id } , { $mul : { order_total : discount } }, session = my_session ) session.end_transaction()
- 14. { order_id, customer_id, line_iems: [ { name : , price : , qty : , } ] }
- 15. db.orders.update( { order_id : my_order_id }, { $mul : { order_total : discount, "line_items.$[].price" : discount } } ) { order_id, customer_id, line_iems: [ { name : , price : , qty : , } ] }
- 16. Distinct business objects Rollups / Views Coming soon: change shard keys
- 18. 4.0
- 21. Relationships { order_id, line_items: [ … ], } { product_id, inventory } REFERENCE
- 22. Relationships EMBEDDED { order_id, line_items: [ { product_id, qty, subtotal } ] } { order_id, line_items: [ … ], } { product_id, inventory } REFERENCE
- 25. MongoDB is the best database for relationships
- 26. Natural Dynamic schema Query language Native drivers Document model
- 27. High Availability Scale-out Workload isolation Zoned sharding Distributed systems
- 29. The best database for modern applications Distributed Systems Runs EverywhereDocument Model Any use case, any platform
- 31. db.products.find().limit(1).pretty() { "_id" : ObjectId("5b116f1b3e1c824cb7950480"), "id" : "298157062", "name" : "Uptown Laptop TSA-Friendly Backpack", "sku" : "MON25232000", "image" : { "large" : "/images/products/bags/large_backpack.jpg", "thumb" : "/images/products/bags/thumb_backpack.jpg" }, "color" : "black", "inventory" : 100, "category" : [ "products", "bags", "backpack", "travel" ], "price" : NumberDecimal("1233423"), "reviews" : [ ], "likes" : 101, "tweets" : 13, "type" : "backpack"
- 35. DEMO Atlas Data Explorer Jonathan Balsano
- 38. grep -o "[0-9]+ms" <filename> | sort -n | tail -n 20 | uniq | xargs -n 1 -I x grep x <filename>
- 40. db.logs.aggregate( [ { $sort : { time : -1 } }, { $limit : 20 }, { $group : { _id : "$queryShape", count : { $sum : 1 } } } ] )
- 47. DEMO Aggregation Pipeline Builder Asya Kamsky
- 51. Categories: S shirts hats socks https://api.swagstore.com/products?cat=shirts db.products.find( { category : "shirts" } )
- 52. Categories: S shirts hats socks Brands: IBM S MongoDB https://api.swagstore.com/products?cat=shirts&brand=mongodb db.products.find( { category : "shirts", brand : "mongodb" } )
- 53. Categories: S shirts hats socks Brands: IBM S MongoDB Price: …api.swagstore.com/products?cat=shirts&brand=mongodb&priceMin=10&priceMax=120 $Min $Max G O db.products.find( { category : "shirts", brand : "mongodb", price : { $lt : 120, $gt: 10 } } )
- 54. Categories: S shirts hats socks Brands: IBM S MongoDB Price: Price: Low to High …ducts?cat=shirts&brand=mongodb&priceMin=10&priceMax=120&sort=price&order=asc $Min $Max G O db.products.find( { category : "shirts", brand : "mongodb", price : { $lt : 120, $gt: 10 } } ).sort( { price : 1 } )
- 55. Categories: S shirts hats socks Brands: IBM S MongoDB Price: Rating: …mongodb&priceMin=10&priceMax=120&sort=price&order=asc&sort2=rating&order2=desc $Min $Max G O db.products.find( { category : "shirts", brand : "mongodb", price : { $lt : 120, $gt: 10 } } ).sort( { price : 1, rating : -1 } ) ?!
- 56. db.products.find( { category : "shirts", brand : "mongodb", price : { $lt : 120, $gt: 10 } } ).sort( { price : 1, rating : -1 } ) Categories: S shirts hats socks Brands: IBM S MongoDB Price: Rating: …mongodb&priceMin=10&priceMax=120&sort=price&order=asc&sort2=rating&order2=desc $Min $Max G O MQL REST
- 57. db.products.find( { category : "shirts", brand : "mongodb", price : { $lt : 120, $gt: 10 } } ).sort( { price : 1, rating : -1 } ) Categories: S shirts hats socks Brands: IBM S MongoDB Price: Rating: …mongodb&priceMin=10&priceMax=120&sort=price&order=asc&sort2=rating&order2=desc $Min $Max G O REST (Shitty Query Language)
- 58. Categories: S shirts hats socks Brands: IBM S MongoDB Price: Rating: $Min $Max G O db.products.find( { category : "shirts", brand : "mongodb", price : { $lt : 120, $gt: 10 } } ).sort( { price : 1, rating : -1 } )
- 59. The serverless platform for building modern applications
- 62. Atlas Stitch Native SDK Auth Rules
- 63. Fully integrated authentication Declarative rules Full MongoDB query language
- 75. BI 2.5 ChartsODBC Driver
- 77. DEMO ODBC & Charts Grigori Melnik
- 78. Download a public beta from mongodb.com/charts Play, learn, provide your feedback! Happy charting!
- 79. Atlas CRUD Aggregation Pipeline Builder Stitch QueryAnywhere Analytics
- 87. DEMO Atlas Global Clusters Andrew Davidson
- 91. # Subscribe to change notifications in a collection. cursor = client.my_db.my_collection.watch([ {'$match': {'operationType': {'$in': [ 'insert', 'replace' ] } }}, {'$match': {'fullDocument.n': {'$gte': 1}}} ]) # Loops forever. for change in cursor: print(change['fullDocument'])
- 93. QueryAnywhere Functions Stitch Triggers
- 99. DEMO Stitch DB Triggers Jane Fine
- 101. QueryAnywhere Functions Stitch Triggers
- 104. M0
- 109. DEMO Ops Manager / Kubernetes James Broadhead
- 111. final Barcode barcode = data.getParcelableExtra(BarcodeActivity.BARCODE_FIELD); final Document query = new Document("barcodeId", barcode.displayValue); final Document update = new Document("$inc", new Document("itemsScanned", 1)); final Document after = itemsColl.findOneAndUpdate( query, update, new FindOneAndUpdateOptions(). upsert(true). returnDocument(ReturnDocument.AFTER));
- 112. final Barcode barcode = data.getParcelableExtra(BarcodeActivity.BARCODE_FIELD); final Document query = new Document("barcodeId", barcode.displayValue); final Document update = new Document("$inc", new Document("itemsScanned", 1)); final Document after = itemsColl.findOneAndUpdate( query, update, new FindOneAndUpdateOptions(). upsert(true). returnDocument(ReturnDocument.AFTER));
- 116. Mobile sync architecture Stitch Mobile: Sync Change Streams Atlas Stitch
- 117. Mobile SyncQueryAnywhere Functions Stitch Triggers
- 118. Atlas free tier on Google Cloud Platform Cross-cloud Kubernetes Mobile Sync
- 120. CRUD Global Clusters Free Tier on GCP Enterprise security features Sharding import
- 121. Query enhancements Free monitoring Multi-document ACID transactions
- 122. Best database for modern applications
- 123. M040 course call-out
- 125. Innovation Award Winners Global Go-to-Market Partner of the Year The Enterprise Launch Fast Scale Data-Driven Business Customer Experience Healthcare Internet of Things Delivery Partner of the Year The William Zola Award for Community Excellence Atlas Savvy Startup
Editor's Notes
- #27: Best way to work with data This is the first of three ____ that make MDB the best database platform for most applications.
- #40: Aggregation
- #43: Create stage-by-stage See documents each time
- #44: Create stage-by-stage See documents each time
- #45: Create stage-by-stage See documents each time
- #46: Create stage-by-stage See documents each time
- #47: Create stage-by-stage See documents each time
- #49: AVAILABLE TODAY
- #50: The agg framework is really powerful, but in some cases its hard to get access to it, like in a web browser.
- #60: beta last year
- #61: beta last year
- #62: beta last year
- #63: beta last year
- #64: beta last year
- #67: beta last year
- #74: So now that you’ve great stuff in your database, you also want to get additional business value from thata data.
- #75: The heart of analytics in MDB is the agg pipeline, but people/analsyts want a more "bueinessy" tool
- #76: WHAT BI FEATURES – AVAILABLE NOW ODBC! I can connect e xceltto atlas in minutes – AVAILBLE NOW Charts
- #80: New in Working with Data
- #81: So documents are the 1st pillar, disctribuets sytems are the second Control over where your data goes Why distribuetd db: Async Streaming, Services, Cloud, Globally distribuetd
- #83: Geo distribution
- #84: 1) Ny 2) add +emea 3) +australia This is suoer powerful, impossiblr with any other tool on the planet, but stt a lot to manage Wouldn’t it be nic….
- #85: 1) Ny 2) add +emea 3) +australia This is suoer powerful, impossiblr with any other tool on the planet, but stt a lot to manage Wouldn’t it be nic….
- #86: 1) Ny 2) add +emea 3) +australia This is suoer powerful, impossiblr with any other tool on the planet, but stt a lot to manage Wouldn’t it be nic….
- #87: This is possible with zoned sharding, super powerful… but a burden to maintain
- #89: This is possible with zoned sharding, super powerful… but a burden to maintain
- #90: THINK HOW HARD BEFORE Atlas global writes clusters are availabele right now. In 3.6, we added chang streams
- #91: Give you:….
- #92: talk about architecture you have to add
- #93: Triggers for the modern, distributed world
- #94: Triggers for the modern, distributed world
- #95: FUNCTIONS!
- #96: FUNCTIONS!
- #97: FUNCTIONS!
- #98: FUNCTIONS!
- #99: FUNCTIONS!
- #102: Stitch Triggers GA today
- #103: New in Distributing Data
- #107: Atlas x-cloud clusters
- #111: On prem is first-class
- #112: On prem is first-class
- #113: On prem is first-class
- #119: Everywhere!