1.
node-crate: node.js & big data
by Stefan Thies

2.
The path is the goal

3.
2000-2013
www.verint.com
Dev Team Lead, Product Management,
Sales Engineer
since 2013
Consulting / Outsourcing
bigdata-analyst.de
just started …
DevOps Evangelist @
www.sematext.com
follow me @seti321
about me

4.
Product evaluations
MarkLogic*
MongoDB*
Elas1csearch*
CouchDB*
CRATE*
0*
10*
20*
30*
40*
50*
60*
70*
80*
90*
Document)oriented)data)stores)Points)for)product)evalua4on)criterias)of)the)specific)project)(RT,)scalability,)replica4on,))features)and)commercial))
Datenreihe1*

5.
How do I get here?
• 2012-2014 Systems with Elasticsearch &
• Mobile Apps (Geo) with Appcelerator Titanium
• Data enrichment & Webcrawlers (whois, geo, appstores)
• Distributed Regex-Processing for CyberSec with 0MQ
• Security Layer around Elasticsearch (sails.js)
• … we did almost everything in NodeJS

6.
Design criterias
• Scalable & lean architecture
• Operations: NO Zoo of 3rd party
components
• We choosed Elasticsearch at that time
• Automatic installation, Docker
• One Language: JavaScript / Node.js

7.
Security
& Admin
- Policies, Users, Roles
- REST API
- Websockets / RT

8.
„data enrichment“
• Hey, we got Elasticsearch - lookup queries for ‚static‘ data sources will be fast!
• Distributed processing based on 0MQ (pull/push) - high throughput, parallel
processing, distributed worker processes
collection
Information
extraction and
processing
data lookups Elasticsearch
Information
extraction and
processing
data lookups Elasticsearch

9.
any problem?
collect
mass data
Elastic
search
Analyze &
Visualize
other data
sources
Geo
Company
data
Open Source
Information
massive updates!
processing
queue / workers
Reporting (PDF)
Accurate Counts
(Facets) -> Aggregation

10.
OPS issues
alternative ‚any‘ DB (for updates) + ES
• It’s a big mess regarding compatibility, maintenance and monitoring all components -
each box can be multiple machines, River might not be updated to latest DB or ES
version, a bug might force you to upgrade one of the components and there the trouble
of dependency starts …
• Reporting: custom programming DSL Queries, Rendering HTML with PhantomJS to
PDF - painful if you know standard Report generators from SQL world. How to tell the
customer to adapt it to his needs? Using some ‚standard‘ DB (SQL or NoSQL)
supported by the reporting tools would solve it.
DB
Vx.x
Data-Procssing
Services
DB-River
V y.y
Elasticsearch
V z.z
Search & Analytics
V. b.b

11.
Don’t panic
google like …

12.
A match at Slideshare!
• An early presentation of
from Jodok got my attention
• http://www.crate.io

13.
• The Mountain Hackathon 2014
birthday of node-crate

14.
Package status
• Igor Likhamanov
• Stefan Thies
• Martin Heidegger
joined recently and made
high professional quality
improvements!

15.
DevOps: Stack-Shrinking
• From 3 down to 1 storage service:
DB
Vx.x
Data-
Processing
DB-River
V y.y
Elasticsearch
V z.z
Search & Analytics
V. b.b
Crate
V a.a
Search & Analytics
V. b.b
Data-
Processing

16.
Data Enrichment Performance
• Elasticsearch has no „update by query“
• If we need to update e.g. 50.000 records it means running a query to identify the relevant
records and send 50.000 HTTP requests for update or build a a large bulk update
request with 50.000 instructions -> overhead! -> K.O
• In Crate
• update something where something_else = ‚other_value’
• ONE command, still a heavy operation because of Lucene delete/index BUT
not ’50.000 commands/network roundtrips’ on top …

17.
Data Enrichment - performance
collect
mass data
CRATE
data store
Analyze &
Visualize
other data
sources
Geo …
Open Source
Information
massive updates, no issue :)
processing
queue / workers
Reporting (PDF)
using CRATE JDBC

18.
BLOB’s
(Images, videos, packet data, …)
• Traditionally
• Meta-Data in DB + Files in some filesystem / separate object storage
• Both behave different for scaling
• Crate stores BLOB’s like other shards including replicas
• More nodes more capacity, replicas etc.
• BLOB storage scales with the data store
• Would be perfect for ‚dropbox‘ like service :) or any archived data

19.
Demo: Installation, usage,
examples walk through …
• https://www.youtube.com/watch?v=ZaDFrd4ZwQk (setup)
• https://github.com/megastef/node-crate (node-crate on github)
• http://techblog.bigdata-analyst.de (sample applications)
• https://crate.io/docs/stable/ (documentation of CRATE.IO)

20.
Simple Example

21.
Import Data (bulk insert)
COPY web_log FROM ‚/var/logs/web_log.json‘
WITH (bulk_size=15000, concurrency=2)

22.
create table web_log
(ts timestamp, host
string, …);
Special data types for
- IP
- Geo Shapes
- Objects (dynamic)

23.
insert into web_log
(ts,useragent, ..)
values (132323,
‚Safari‘, …)

24.
select
update

25.
Anything missing?
• „Kibana“
• see my blog how to add it (‚officially‘ not supported)
• Performance monitoring
• see next section …

26.
Using Kibana with Crate

27.
Performance Monitoring

28.
Setup & Run
If you can’t measure it
you can’t fix it!

29.
Monitoring -
Sematext SPM supported Applications
+
Release status for CRATE/SPM monitor: Prototype
pls. call me upon demand
NEW

30.
SPM Monitoring

31.
My NPM Modules
• node-crate - DB driver for Crate for NodeJS - help for ‚Waterline/sails.js‘
ORM appreciated! We are open for other suggestions, we like sails.js
Websocket capability and security features (policies) and would get that ‚for
free‘
• winston-crate - logger transport for Crate using node-crate
• bro-ids - simple interface to the BRO intrusion detection system (IP
Monitoring)

32.
+ sematext related work
• node-red-contrib-logsene - Node-Red (IoT, MQTT, …) - Logger for Logsene
• node-spm - Custom Metrics & Logging API for http://www.sematext.com
adapted for NodeJS
• spmagent - Performance Monitoring for Node.js
• Garbage Collection, Event Loop Monitor, HTTP Metrics, Cluster mode, …
• Release: Very Soon! - Feb 2015 - stefan.thies@sematext.com for early access

33.
Dig
Search?
Dig
Analy0cs?
Dig
Big
Data?
Dig
Performance?
Dig
Logging?
Dig
working
with
open
–
source?
We‘re
hiring
planet
-­‐
wide!
h2p://www.sematext.com/about/jobs.html

34.
Thank you for your attention.
03.03.15 DevOps Frankfurt
“Metrics & more …”