mongodb 101 & beyond: get started in mongodb 3.0, preview 3.2 & demo of ops manager, muthu...

MongoDB 3.x & Ops Manager

Muthu ChinnasamySenior Solutions Architectmuthu@mongodb.com

MongoDB is for…

Some of the Giant Ideas Using MongoDB

MongoDB Adds Business Value

Competitive Advantage Mitigating Risk

Lower TCOFaster Time to Value

Agenda

• What's new in MongoDB 3.0?• Ops manager - Automation, backup,

monitoring• What's new in version 3.2?• Q&A

What's new in MongoDB 3.0?

Pluggable Storage Engines

Pluggable Storage Engines

Content Repo

IoT Sensor Backend Ad Service Customer

Analytics Archive

MongoDB Query Language (MQL) + Native Drivers

MongoDB Document Data Model

MMAP V1 WT In-Memory ? ?

Supported in MongoDB 3.0 Future Possible Storage Engines

Man

agem

ent

Sec

urity

Example Future State

Experimental

Introducing WiredTiger

• Pluggable storage engines!• MMAPv1 (Default)• wiredTiger

Additional flag when launching 3.0.x mongod:

--storageEngine=wiredTiger

How Do I run WiredTiger?

• Cannot copy raw data files. WT will fail to start if it finds wrong data format

• Two ways to perform an engine upgrade:• Mongodump/Mongorestore• Add new replica member with WT

• You can run replicas with mixed storage engines

How Do I Upgrade to it?

• Document-level concurrency• Compression• Consistency without journaling• Better performance for write heavy

workloads• Vertically scalable as it allows full hardware

utilization• Index placement on faster storage devices

Why is WiredTiger Awesome?

mmapv1 2.6 concurrency model

Lock manager has a toll booth for each database

Reads and writes must acquire database level lock

mmapv1 3.0 concurrency model

Lock manager has a toll booth for each collection

Reads and writes must acquire collection level lock

7-10x Better Write Performance

No toll booths!Atomic update replaces latching/lockingYields on write contention to same document

Up to 80% Compression

• WiredTiger uses snappy compression by default in MongoDB

• Supported compression algorithms – snappy [default]: good compression, low overhead– zlib: better compression, more CPU– none

• Indexes are compressed using prefix compression– allows compression in RAM

500GB 100GB

Compression – mongod options

--wiredTigerCollectionBlockCompressor (=snappy)

[snappy|zlib|none]

--wiredTigerJournalCompressor (=snappy)

--wiredTigerIndexPrefixCompression (=1)

Compression – Object options

db.createCollection( "coll", {storageEngine: {wiredTiger: { configString: "block_compressor=snappy" }}})

db.coll.createIndex({a:1},{storageEngine: {wiredTiger: { configString: "block_compressor=zlib"}}})

• WiredTiger cache stores uncompressed data• Ideally, working set fits in WT cache

1. File system cache stores compressed data2. Uses higher value of 50% of RAM or 1GB

WiredTiger Cache

--wiredTigerCacheSizeGB {arg}

Ensure indexes fit in RAM

Ops Manager

How Ops Manager Helps You

Scale EasilyMeet SLAs

Best Practices, Automated

Cut Management Overhead

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Zero Downtime Cluster UpgradesManual Steps

• Manual steps upgrading a 2.6.11 sharded cluster to 3.0.6 version, on enterprise edition, and convert the storage engine to wiredTiger

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Upgrades, downgrades150+ steps

Example Deployment – 6 Servers

Zero Downtime Cluster UpgradesOps Manager Automation

• Using Ops Manager automation• Start with a 2.6.11 Community cluster• Upgrade to 3.0.6 Enterprise cluster• Convert storage Engine to wiredTiger

Turn long and complicated manual processes into single click operations with Ops Manager automation

Ensure availability during system upgrades

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Summary: Benefits of MongoDB 3.0

What's new in version 3.2

New in MongoDB 3.2

MongoDB 3.2 New Features

• Fast failovers– 2-seconds election times

• Support for more than 3 data centers– Config servers as replica sets

• Cluster read-committed– readConcern: { level: <majority|local>

• WiredTiger default storage engine• Aggregation framework enhancements

– New stages $sample– New arithmetic operators & accumulators

• Mongo shell enhancements

MongoDB 3.2 – Compass

MongoDB 3.2 – Left Outer Joins• Create a new field in aggregated documents "cust_orders"

containing array of documents from "orders" collection • Similar to where "customers"."_id"="orders"."cust_id"

Db.customers.aggregate([ {

$lookUp: { from: "orders", localField: "_id", foreignField: "cust_id", as: "cust_orders" }

}])

MongoDB 3.2 – Encryption at rest

• Encryption is a database-level option– Master key & local keys allow for easier key

management and key rotation for compliance• Supports standard 3rd party key management

appliances (KMIP)• Default encryption schema is AES256-CBC

– Also have GCM• FIPS 140-2 compliant option

MongoDB 3.2 – Partial Indexes

> db.customers.createIndex({ state:1}, { partialFilterExpression: { active: {$eq : 'Y'}}}){

"createdCollectionAutomatically" : false,"numIndexesBefore" : 1,"numIndexesAfter" : 2,"ok" : 1

}Index only for docs matching the filter

expression

MongoDB 3.2 – Document Validation> db.runCommand({"collMod": 'customers', "validator" : {email: {$exists: true}}}){ "ok" : 1 }

> db.customers.insert({name:'Rose McClendon', age:27, state:'CA', city:'San Francisco', zip:94301})

WriteResult({"nInserted" : 0,"writeError" : {

"code" : 121,"errmsg" : "Document failed validation"

}})

> db.customers.insert({name:'Rose McClendon', age:27, email:'rose.mcclendon@cox.net', state:'CA', city:'San Francisco', zip:94301})WriteResult({ "nInserted" : 1 })

Enforces email field

Thank You!

Questions?