MongoDB Europe 2016 - Star in a Reasonably Priced Car - Which Driver is Best?

MongoDB’s best driver John Page - Principal Consulting Engineer

The nature of Drivers

#MDBE16

What does a MongoDB Driver do?

•  Idiomatic API • Service Discovery and High Availability •  Authentication • Wire protocol version abstraction

This is non trivial work – drivers are not thin wrappers.

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What does a MongoDB Driver do?

•  Idiomatic API • Service Discovery and High Availability •  Authentication • Wire protocol version abstraction

#MDBE16

What Languages have Drivers

Python

Perl JavaScript

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Idiomatic API - Write

Data Source

Map / Object

db.coll.insert(Map)

BSON Bytes

TCP Data

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Idiomatic API - Read

TCP

Data BSON Bytes

db.coll.find()

Map / Object

Field Value

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Idiomatic API – Read Optimisations

TCP

Data BSON Bytes

db.coll.find()

Field Value

Lazy BSON

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High Data Throughput Workloads

• Data Loading • Data Conversion • External Analysis / Reporting • Sensors and Internet Things

Reads/Writes from 10s to 100s MB/s

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Motivation for Measuring this

• POC Benchmark stories •  Shell Loops •  YCSB

• Consulting Experiences •  Application Benchmarks and Sizing

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Quick Summary

• Drivers do a number of things. • Different Languages need different things done. •  Languages can vary in costs to write, maintain and run. • We want to know the relative difference for the run part.

Designing a Benchmark

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Things to be aware of

• Experience. •  It’s a non trivial undertaking.

• Bias and Benchmarketing. •  Be aware of conscious and unconscious bias. •  Seek Assistance and Consensus.

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Our Client Benchmark

CRU (!D) •  Insert 1,000,000 ~8K records. • Retrieve 1 field from each from the DB. • Modify each changing each String field.

Not using Aggregation, Projection or update modifiers.

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Architecture

Client (Fixed and Smallish)

•  4 Xeon 2.5GHz CPU cores • 16GB RAM • 10GB/s Network to server. • 10GB/s switch

Server

• MongoDB 3.2 • WiredTiger – no journal •  Local SSD • 32 Xeon 2.5GHz Cores •  250GB RAM • 10GB/s Network to client.

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Measurables

What numbers are we interested in

• Straight line speed. •  Single Thread

•  Create (records/s) •  Read (records/s) •  Update (records/s)

• Max throughput. •  Multi Thread/Process (records/s)

Results

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Javascript – Mongo Shell and Node.JS

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

Shell Linear Shell Parallel Node.js linear Node.js Parallel

Operations per Second

Create Read Update

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0

10000

20000

30000

40000

50000

60000

70000

80000

90000



Create Read Update

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0

5000

10000

15000

20000

25000

30000



Create Read Update

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Node versus Python– the hipster dichotomy

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5000

10000

15000

20000

25000

30000

Node.js linear Node.js Parallel


Create Read Update

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Node versus Python– the hipster dichotomy

0

5000

10000

15000

20000

25000

30000

Node.js linear Node.js Parallel Python linear Python parallel


Create Read Update

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Node versus Python with C extensions

0

5000

10000

15000

20000

25000

30000

Node.js linear Node.js Parallel Python w. C linear Python w. C parallel


Create Read Update

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Java 8 – the corporate favourite

0

5000

10000

15000

20000

25000

30000

35000

40000

Java 8 linear Java 8 parallel


Create Read Update

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Java 8 on Linux versus Java 8 on Windows

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5000

10000

15000

20000

25000

30000

35000

40000

Java 8 linear Java 8 parallel Java 8 linear(win) Java 8 parallel (win)


Create Read Update

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Java 8 on Windows versus C#

0

5000

10000

15000

20000

25000

30000

35000

40000

Java 8 linear(win) Java 8 parallel (win) C# linear C# parallel


Create Read Update

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Java 8 on Windows versus C#

0

5000

10000

15000

20000

25000

30000

35000

40000

Java 8 linear(win) Java 8 parallel (win) C# linear C# parallel


Create Read Update

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C# on Windows versus C# on Linux!

0

5000

10000

15000

20000

25000

30000

35000

40000

C# linear C# parallel Dotnet Core liner DotNet Core Parallel


Create Read Update

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Java 8 on Linux versus Morphia ODM

0

5000

10000

15000

20000

25000

30000

35000

40000

Java 8 linear Java 8 parallel Morphia linear Morphia parallel


Create Read Update

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C – the classic choice

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

C linear C Parallel


Create Read Update

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C – the classic choice versus Go ‘The new C’

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

C linear C Parallel GoLang Linear GoLang Parallel


Create Read Update

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Java 8 on Linux versus C

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

Java 8 linear Java 8 parallel C linear C Parallel

Operation per Second

Create Read Update

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Java 8 on Linux versus PHP 7 – the surprise

0

5000

10000

15000

20000

25000

30000

35000

40000

Java 8 linear Java 8 parallel PHP 7 linear PHP 7 parallel


Create Read Update

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Create speed

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

C Java Threaded PHP 7 Java (on Win) GoLang Morphia Python with C Extensions

Node.JS CSharp


Create

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Read speed

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

C Shell PHP 7 Java Threaded Python with C Extensions

Java (on Win) GoLang Node.JS Morphia

Operations per Second.

Read

What does that mean?

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Back in the real world

• Database backend upgrade for logistics company •  Schema conversion •  Unacceptable 8 hours of downtime planned •  Rewrite in C •  40 mins downtime.

• Regular bulk load of JSON Ecommerce data (>500GB) •  From 35 minutes using mongoimport ( written in Go ) •  To 7 minutes with custom loader.

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Don’t be British!

•  If you aren’t using one ‘fast’ language, maybe you should. •  If you aren’t using one dynamic language – go experience the joy. • Be a polyglot when you are working with MongoDB.

•  The API’s are really similar to make it easy.

•  A single language SLOW and LOUD isn’t always best.

Data & Analytics

MongoDB Europe 2016 - Star in a Reasonably Priced Car - Which Driver is Best?