SlideShare a Scribd company logo
1 of 51
Download to read offline
Robert	Hryniewicz
Data		Evangelist
@RobHryniewicz
Hands-on	Intro	to	Spark	&	Zeppelin
Crash Course
2 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
The	“Big	Data”	Problem
à A	single	machine	cannot	process	or	even	store	all	the	data!
Problem
Solution
à Distribute	data	over	large	clusters
Difficulty
à How	to	split	work	across	machines?
à Moving	data	over	network	is	expensive
à Must	consider	data	&	network	locality
à How	to	deal	with	failures?
à How	to	deal	with	slow	nodes?
3 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	Background
4 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Access	Rates
At	least	an	order	of	magnitude	difference	between	memory	and	hard	drive	/	network	speed
FAST slow slow
5 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
What	is	Spark?
à Apache	Open	Source	Project - originally	developed	at	AMPLab (University	of	California	
Berkeley)
à Data	Processing	Engine - focused	on	in-memory	distributed	computing	use-cases
à API - Scala,	Python,	Java	and	R
6 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	Ecosystem
Spark	Core
Spark	SQL Spark	Streaming MLLib GraphX
7 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Why	Spark?
à Elegant	Developer	APIs
– Single	environment	for	data	munging and	Machine	Learning	(ML)
à In-memory	computation	model	– Fast!
– Effective	for	iterative	computations	and	ML
à Machine	Learning
– Implementation	of	distributed	ML	algorithms
– Pipeline	API	(Spark	ML)
8 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
History	of	Hadoop &	Spark
9 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Apache	Spark	Basics
10 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	Context
à Main	entry	point	for	Spark	functionality
à Represents	a	connection	to	a	Spark	cluster
à Represented	as	sc in	your	code
What	is	it?
11 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
RDD	- Resilient	Distributed	Dataset
à Primary	abstraction	in	Spark
– An	Immutable collection	of	objects	(or	records,	or	elements)	that	can	be	operated	on	in	parallel
à Distributed
– Collection	of	elements	partitioned across	nodes	in	a	cluster
– Each	RDD	is	composed	of	one	or	more	partitions
– User	can	control	the	number	of	partitions
– More	partitions	=>	more	parallelism	
à Resilient
– Recover	from	node	failures
– An	RDD	keeps	its	lineage	information	->	it	can	be	recreated	from	parent	RDDs
à Created	by	starting	with	a	file	in	Hadoop Distributed	File	System	(HDFS)	or	an	existing	
collection	in	the	driver	program
à May	be	persisted in	memory	for	efficient reuse across	parallel	operations	(caching)
12 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
RDD	– Resilient	Distributed	Dataset
Partition	
1
Partition	
2
Partition	
3
RDD	2
Partition	
1
Partition	
2
Partition	
3
Partition	
4
RDD	1
Cluster
Nodes
13 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	SQL
14 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	SQL	Overview
à Spark	module	for	structured	data	processing	(e.g.	DB	tables,	JSON	files)
à Three	ways	to	manipulate	data:
– DataFrames API
– SQL	queries
– Datasets	API	
à Same	execution	engine	for	all	three
à Spark	SQL	interfaces provide	more	information	about	both	structure and	computation
being	performed	than	basic	Spark	RDD	API
15 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
DataFrames
à Conceptually equivalent to	a	table	in	relational	DB	or	data	frame	in	R/Python
à API	available	in	Scala,	Java,	Python,	and	R
à Richer	optimizations	(significantly	faster	than	RDDs)
à Distributed	collection	of	data	organized	into	named	columns
à Underneath	is	an	RDD
16 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
DataFrames
CSVAvro
HIVE
Spark	SQL
Text
Col1 Col2 … … ColN
DataFrame
(with	RDD	underneath)
Column
Row
Created	from	Various	Sources
à DataFrames from	HIVE:
– Reading	and	writing	HIVE	tables,	
including	ORC
à DataFrames from	files:
– Built-in:	JSON,	JDBC,	ORC,	Parquet,	HDFS
– External	plug-in:	CSV,	HBASE,	Avro
à DataFrames from	existing	RDDs
– with	toDF()function
Data	is	described	as	a	DataFrame
with	rows,	columns	and	a	schema
17 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
SQL	Context	and	Hive	Context
à Entry	point	into	all	functionality	in	Spark	SQL
à All	you	need	is	SparkContext
val sqlContext = SQLContext(sc)
SQLContext
à Superset	of	functionality	provided	by	basic	SQLContext
– Read	data	from	Hive	tables
– Access	to	Hive	Functions	à UDFs
HiveContext
val hc = HiveContext(sc)
Use	when	your	
data	resides	in	
Hive
18 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	SQL	Examples
19 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
DataFrame Example
val df = sqlContext.table("flightsTbl")
df.select("Origin", "Dest", "DepDelay").show(5)
Reading	Data	From	Table
+------+----+--------+
|Origin|Dest|DepDelay|
+------+----+--------+
| IAD| TPA| 8|
| IAD| TPA| 19|
| IND| BWI| 8|
| IND| BWI| -4|
| IND| BWI| 34|
+------+----+--------+
20 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
DataFrame Example
df.select("Origin", "Dest", "DepDelay”).filter($"DepDelay" > 15).show(5)
Using	DataFrame API	to	Filter	Data	(show	delays	more	than	15	min)
+------+----+--------+
|Origin|Dest|DepDelay|
+------+----+--------+
| IAD| TPA| 19|
| IND| BWI| 34|
| IND| JAX| 25|
| IND| LAS| 67|
| IND| MCO| 94|
+------+----+--------+
21 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
SQL	Example
// Register Temporary Table
df.registerTempTable("flights")
// Use SQL to Query Dataset
sqlContext.sql("SELECT Origin, Dest, DepDelay
FROM flights
WHERE DepDelay > 15 LIMIT 5").show
Using	SQL	to	Query	and	Filter	Data	(again,	show	delays	more	than	15	min)
+------+----+--------+
|Origin|Dest|DepDelay|
+------+----+--------+
| IAD| TPA| 19|
| IND| BWI| 34|
| IND| JAX| 25|
| IND| LAS| 67|
| IND| MCO| 94|
+------+----+--------+
22 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
RDD	vs.	DataFrame
23 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
RDDs	vs.	DataFrames
RDD
DataFrame
à Lower-level	API	(more	control)
à Lots	of	existing	code	&	users
à Compile-time	type-safety
à Higher-level	API	(faster	development)
à Faster	sorting,	hashing,	and	serialization
à More	opportunities	for	automatic	optimization
à Lower	memory	pressure
24 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Data Frames are Intuitive
RDD Example
Equivalent Data Frame Example
dept name age
Bio H	Smith 48
CS A	Turing 54
Bio B	Jones 43
Phys E Witten 61
Find	average	age	by	
department?
25 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	SQL	Optimizations
à Spark	SQL	uses	an	underlying	optimization	engine	(Catalyst)
– Catalyst	can	perform	intelligent	optimization	since	it	understands	the	schema
à Spark	SQL	does	not	materialize	all	the	columns	(as	with	RDD)	only	what’s	needed
26 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Catalyst:	Spark	SQL	optimizer
à Query	or	data	frame	operations	modeled	as	a	tree
à Logical	plan	created	and	optimized
à Various	physical	plans	created;	best	plan	chosen
à Code	generation	and	execution
27 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	Streaming
28 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	Streaming
à Extension	of	Spark	Core	API
à Stream	processing	of	live	data	streams
– Scalable
– High-throughput
– Fault-tolerant
Overview
29 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	Streaming
30 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Spark	Streaming
à Apply	transformations	over	a	sliding	window	of	data,	e.g.	rolling	average
Window	Operations
31 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Apache	Zeppelin	&	HDP	Sandbox
32 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Apache	Zeppelin	– A	Modern	Web-based	Data	Science	Studio
à Data	exploration	and	discovery
à Visualization
à Deeply	integrated	with	Spark	and	Hadoop
à Pluggable	interpreters
à Multiple	languages	in	one	notebook:	R,	Python,	Scala
33 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
34 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
35 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
36 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
What’s	not	included	with	Spark?
ResourceManagement
Storage
Applications
Spark	Core	Engine
Scala
Java
Python
libraries
MLlib	
(Machine	
learning)
Spark	
SQL*
Spark	
Streaming*
Spark	Core	Engine
37 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
HDP	Sandbox
What’s	included	in	the	Sandbox?
à Zeppelin	
à Latest	Hortonworks	Data	Platform	(HDP)
– Spark
– YARN	à Resource	Management
– HDFS	à Distributed	Storage	Layer
– And	many	more	components... YARN
Scala
Java
Python
R
APIs
Spark Core Engine
Spark
SQL
Spark
Streaming
MLlib GraphX
1 ° ° ° ° ° ° ° ° °
° ° ° ° ° ° ° ° ° °
°
N
HDFS
38 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Access patterns enabled by YARN
YARN: Data Operating System
1 ° ° ° ° ° ° ° ° °
° ° ° ° ° ° ° ° °
°
°N
HDFS
Hadoop Distributed File System
Interactive Real-TimeBatch
Applications Batch
Needs to happen but, no
timeframe limitations
Interactive
Needs to happen at
Human time
Real-Time
Needs to happen at
Machine Execution time.
39 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Why	Spark	on	YARN?
à Utilize	existing	HDP	cluster	infrastructure
à Resource	management	
– share	Spark	workloads	with	other	workloads	like	PIG,	HIVE,	etc.
à Scheduling	and	queues
Spark	Driver
Client
Spark
Application	Master
YARN	container
Spark	Executor
YARN	container
Task Task
Spark	Executor
YARN	container
Task Task
Spark	Executor
YARN	container
Task Task
40 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Why HDFS?
Fault Tolerant Distributed Storage
• Divide	files	into	big	blocks	and	distribute	3	copies	randomlyacross	the	cluster
• Processing	Data	Locality
• Not	Just	storage	but	computation
10110100101
00100111001
11111001010
01110100101
00101100100
10101001100
01010010111
01011101011
11011011010
10110100101
01001010101
01011100100
11010111010
0
Logical File
1
2
3
4
Blocks
1
Cluster
1
1
2
2
2
3
3
34
4
4
41 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
There’s more to HDP
YARN : Data Operating System
DATA ACCESS SECURITY
GOVERNANCE &
INTEGRATION OPERATIONS
1 ° ° ° ° ° ° ° ° °
° ° ° ° ° ° ° ° ° °
°
N
Data Lifecycle &
Governance
Falcon
Atlas
Administration
Authentication
Authorization
Auditing
Data Protection
Ranger
Knox
Atlas
HDFS	EncryptionData Workflow
Sqoop
Flume
Kafka
NFS
WebHDFS
Provisioning,
Managing, &
Monitoring
Ambari
Cloudbreak
Zookeeper
Scheduling
Oozie
Batch
MapReduce
Script
Pig
Search
Solr
SQL
Hive
NoSQL
HBase
Accumulo
Phoenix
Stream
Storm
In-memory Others
ISV Engines
Tez Tez Slider Slider
DATA MANAGEMENT
Hortonworks	Data	Platform	2.4.x
Deployment	ChoiceLinux	 Windows	 On-Premise	 Cloud
HDFS Hadoop Distributed File System
42 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
HDP	2.5	TP
43 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
44 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
45 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
View	User	Sessions
46 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Hortonworks	Community	Connection
47 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Hortonworks	Community	Connection
Read access for everyone, join to participate and be recognized
• Full	Q&A	Platform	(like	StackOverflow)
• Knowledge	Base	Articles
• Code	Samples	and	Repositories
48 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Community	Engagement
Participate now at: community.hortonworks.com©	Hortonworks	Inc.	2011	–2015.	All	Rights	Reserved
7,500+
Registered	Users
15,000+
Answers
20,000+
Technical	Assets
One Website!
49 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Lab	Preview
50 ©	Hortonworks	Inc.	2011	–2016.	All	Rights	Reserved
Link	to	Tutorial	with	Lab	Instructions
http://tinyurl.com/hwx-intro-to-spark
Robert	Hryniewicz
@RobHryniewicz
Thanks!

More Related Content

What's hot

Automatic Detection, Classification and Authorization of Sensitive Personal D...
Automatic Detection, Classification and Authorization of Sensitive Personal D...Automatic Detection, Classification and Authorization of Sensitive Personal D...
Automatic Detection, Classification and Authorization of Sensitive Personal D...DataWorks Summit/Hadoop Summit
 
Innovation in the Enterprise Rent-A-Car Data Warehouse
Innovation in the Enterprise Rent-A-Car Data WarehouseInnovation in the Enterprise Rent-A-Car Data Warehouse
Innovation in the Enterprise Rent-A-Car Data WarehouseDataWorks Summit
 
A Comprehensive Approach to Building your Big Data - with Cisco, Hortonworks ...
A Comprehensive Approach to Building your Big Data - with Cisco, Hortonworks ...A Comprehensive Approach to Building your Big Data - with Cisco, Hortonworks ...
A Comprehensive Approach to Building your Big Data - with Cisco, Hortonworks ...Hortonworks
 
Insights into Real World Data Management Challenges
Insights into Real World Data Management ChallengesInsights into Real World Data Management Challenges
Insights into Real World Data Management ChallengesDataWorks Summit
 
Hadoop & Cloud Storage: Object Store Integration in Production
Hadoop & Cloud Storage: Object Store Integration in ProductionHadoop & Cloud Storage: Object Store Integration in Production
Hadoop & Cloud Storage: Object Store Integration in ProductionDataWorks Summit/Hadoop Summit
 
YARN webinar series: Using Scalding to write applications to Hadoop and YARN
YARN webinar series: Using Scalding to write applications to Hadoop and YARNYARN webinar series: Using Scalding to write applications to Hadoop and YARN
YARN webinar series: Using Scalding to write applications to Hadoop and YARNHortonworks
 
Hadoop crash course workshop at Hadoop Summit
Hadoop crash course workshop at Hadoop SummitHadoop crash course workshop at Hadoop Summit
Hadoop crash course workshop at Hadoop SummitDataWorks Summit
 
Webinar turbo charging_data_science_hawq_on_hdp_final
Webinar turbo charging_data_science_hawq_on_hdp_finalWebinar turbo charging_data_science_hawq_on_hdp_final
Webinar turbo charging_data_science_hawq_on_hdp_finalHortonworks
 
Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...
Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...
Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...DataWorks Summit/Hadoop Summit
 
Format Wars: from VHS and Beta to Avro and Parquet
Format Wars: from VHS and Beta to Avro and ParquetFormat Wars: from VHS and Beta to Avro and Parquet
Format Wars: from VHS and Beta to Avro and ParquetDataWorks Summit
 
Achieving a 360-degree view of manufacturing via open source industrial data ...
Achieving a 360-degree view of manufacturing via open source industrial data ...Achieving a 360-degree view of manufacturing via open source industrial data ...
Achieving a 360-degree view of manufacturing via open source industrial data ...DataWorks Summit
 
Predicting Customer Experience through Hadoop and Customer Behavior Graphs
Predicting Customer Experience through Hadoop and Customer Behavior GraphsPredicting Customer Experience through Hadoop and Customer Behavior Graphs
Predicting Customer Experience through Hadoop and Customer Behavior GraphsHortonworks
 
Apache Hadoop YARN: state of the union
Apache Hadoop YARN: state of the unionApache Hadoop YARN: state of the union
Apache Hadoop YARN: state of the unionDataWorks Summit
 
Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...
Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...
Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...Hortonworks
 

What's hot (20)

Automatic Detection, Classification and Authorization of Sensitive Personal D...
Automatic Detection, Classification and Authorization of Sensitive Personal D...Automatic Detection, Classification and Authorization of Sensitive Personal D...
Automatic Detection, Classification and Authorization of Sensitive Personal D...
 
Innovation in the Enterprise Rent-A-Car Data Warehouse
Innovation in the Enterprise Rent-A-Car Data WarehouseInnovation in the Enterprise Rent-A-Car Data Warehouse
Innovation in the Enterprise Rent-A-Car Data Warehouse
 
A Comprehensive Approach to Building your Big Data - with Cisco, Hortonworks ...
A Comprehensive Approach to Building your Big Data - with Cisco, Hortonworks ...A Comprehensive Approach to Building your Big Data - with Cisco, Hortonworks ...
A Comprehensive Approach to Building your Big Data - with Cisco, Hortonworks ...
 
LLAP: Sub-Second Analytical Queries in Hive
LLAP: Sub-Second Analytical Queries in HiveLLAP: Sub-Second Analytical Queries in Hive
LLAP: Sub-Second Analytical Queries in Hive
 
How Hadoop Makes the Natixis Pack More Efficient
How Hadoop Makes the Natixis Pack More Efficient How Hadoop Makes the Natixis Pack More Efficient
How Hadoop Makes the Natixis Pack More Efficient
 
Insights into Real World Data Management Challenges
Insights into Real World Data Management ChallengesInsights into Real World Data Management Challenges
Insights into Real World Data Management Challenges
 
Hadoop & Cloud Storage: Object Store Integration in Production
Hadoop & Cloud Storage: Object Store Integration in ProductionHadoop & Cloud Storage: Object Store Integration in Production
Hadoop & Cloud Storage: Object Store Integration in Production
 
The Elephant in the Clouds
The Elephant in the CloudsThe Elephant in the Clouds
The Elephant in the Clouds
 
YARN webinar series: Using Scalding to write applications to Hadoop and YARN
YARN webinar series: Using Scalding to write applications to Hadoop and YARNYARN webinar series: Using Scalding to write applications to Hadoop and YARN
YARN webinar series: Using Scalding to write applications to Hadoop and YARN
 
Hadoop crash course workshop at Hadoop Summit
Hadoop crash course workshop at Hadoop SummitHadoop crash course workshop at Hadoop Summit
Hadoop crash course workshop at Hadoop Summit
 
Modernise your EDW - Data Lake
Modernise your EDW - Data LakeModernise your EDW - Data Lake
Modernise your EDW - Data Lake
 
Webinar turbo charging_data_science_hawq_on_hdp_final
Webinar turbo charging_data_science_hawq_on_hdp_finalWebinar turbo charging_data_science_hawq_on_hdp_final
Webinar turbo charging_data_science_hawq_on_hdp_final
 
Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...
Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...
Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...
 
Format Wars: from VHS and Beta to Avro and Parquet
Format Wars: from VHS and Beta to Avro and ParquetFormat Wars: from VHS and Beta to Avro and Parquet
Format Wars: from VHS and Beta to Avro and Parquet
 
Achieving a 360-degree view of manufacturing via open source industrial data ...
Achieving a 360-degree view of manufacturing via open source industrial data ...Achieving a 360-degree view of manufacturing via open source industrial data ...
Achieving a 360-degree view of manufacturing via open source industrial data ...
 
Predicting Customer Experience through Hadoop and Customer Behavior Graphs
Predicting Customer Experience through Hadoop and Customer Behavior GraphsPredicting Customer Experience through Hadoop and Customer Behavior Graphs
Predicting Customer Experience through Hadoop and Customer Behavior Graphs
 
Apache Hadoop YARN: state of the union
Apache Hadoop YARN: state of the unionApache Hadoop YARN: state of the union
Apache Hadoop YARN: state of the union
 
Apache Hadoop Crash Course
Apache Hadoop Crash CourseApache Hadoop Crash Course
Apache Hadoop Crash Course
 
Automated Analytics at Scale
Automated Analytics at ScaleAutomated Analytics at Scale
Automated Analytics at Scale
 
Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...
Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...
Optimizing your Modern Data Architecture - with Attunity, RCG Global Services...
 

Viewers also liked

Data Science with Apache Spark - Crash Course - HS16SJ
Data Science with Apache Spark - Crash Course - HS16SJData Science with Apache Spark - Crash Course - HS16SJ
Data Science with Apache Spark - Crash Course - HS16SJDataWorks Summit/Hadoop Summit
 
Kafka含むデータ処理フローを NiFiで構築するさまを実演する5分間
Kafka含むデータ処理フローを NiFiで構築するさまを実演する5分間Kafka含むデータ処理フローを NiFiで構築するさまを実演する5分間
Kafka含むデータ処理フローを NiFiで構築するさまを実演する5分間Koji Kawamura
 
HDF Powered by Apache NiFi Introduction
HDF Powered by Apache NiFi IntroductionHDF Powered by Apache NiFi Introduction
HDF Powered by Apache NiFi IntroductionMilind Pandit
 
Apache NiFiで、楽して、つながる、広がる IoTプロジェクト
Apache NiFiで、楽して、つながる、広がる IoTプロジェクトApache NiFiで、楽して、つながる、広がる IoTプロジェクト
Apache NiFiで、楽して、つながる、広がる IoTプロジェクトKoji Kawamura
 
What the Spark!? Intro and Use Cases
What the Spark!? Intro and Use CasesWhat the Spark!? Intro and Use Cases
What the Spark!? Intro and Use CasesAerospike, Inc.
 
Apache NiFi 1.0 in Nutshell
Apache NiFi 1.0 in NutshellApache NiFi 1.0 in Nutshell
Apache NiFi 1.0 in NutshellKoji Kawamura
 
Togaf introduction and core concepts
Togaf introduction and core conceptsTogaf introduction and core concepts
Togaf introduction and core conceptsPaul Sullivan
 
Apache Hadoop YARN
Apache Hadoop YARNApache Hadoop YARN
Apache Hadoop YARNAdam Kawa
 
Building large scale applications in yarn with apache twill
Building large scale applications in yarn with apache twillBuilding large scale applications in yarn with apache twill
Building large scale applications in yarn with apache twillHenry Saputra
 
Harnessing the power of YARN with Apache Twill
Harnessing the power of YARN with Apache TwillHarnessing the power of YARN with Apache Twill
Harnessing the power of YARN with Apache TwillTerence Yim
 
Apache Hadoop YARN, NameNode HA, HDFS Federation
Apache Hadoop YARN, NameNode HA, HDFS FederationApache Hadoop YARN, NameNode HA, HDFS Federation
Apache Hadoop YARN, NameNode HA, HDFS FederationAdam Kawa
 
Hortonworks Data In Motion Series Part 3 - HDF Ambari
Hortonworks Data In Motion Series Part 3 - HDF Ambari Hortonworks Data In Motion Series Part 3 - HDF Ambari
Hortonworks Data In Motion Series Part 3 - HDF Ambari Hortonworks
 
Learn Togaf 9.1 in 100 slides!
Learn Togaf 9.1 in 100 slides!Learn Togaf 9.1 in 100 slides!
Learn Togaf 9.1 in 100 slides!Sam Mandebvu
 
Real-Time Data Flows with Apache NiFi
Real-Time Data Flows with Apache NiFiReal-Time Data Flows with Apache NiFi
Real-Time Data Flows with Apache NiFiManish Gupta
 

Viewers also liked (20)

Hadoop Summit Tokyo Apache NiFi Crash Course
Hadoop Summit Tokyo Apache NiFi Crash CourseHadoop Summit Tokyo Apache NiFi Crash Course
Hadoop Summit Tokyo Apache NiFi Crash Course
 
Apache spark Intro
Apache spark IntroApache spark Intro
Apache spark Intro
 
Data Science with Apache Spark - Crash Course - HS16SJ
Data Science with Apache Spark - Crash Course - HS16SJData Science with Apache Spark - Crash Course - HS16SJ
Data Science with Apache Spark - Crash Course - HS16SJ
 
Kafka含むデータ処理フローを NiFiで構築するさまを実演する5分間
Kafka含むデータ処理フローを NiFiで構築するさまを実演する5分間Kafka含むデータ処理フローを NiFiで構築するさまを実演する5分間
Kafka含むデータ処理フローを NiFiで構築するさまを実演する5分間
 
HDF Powered by Apache NiFi Introduction
HDF Powered by Apache NiFi IntroductionHDF Powered by Apache NiFi Introduction
HDF Powered by Apache NiFi Introduction
 
Apache NiFiで、楽して、つながる、広がる IoTプロジェクト
Apache NiFiで、楽して、つながる、広がる IoTプロジェクトApache NiFiで、楽して、つながる、広がる IoTプロジェクト
Apache NiFiで、楽して、つながる、広がる IoTプロジェクト
 
What the Spark!? Intro and Use Cases
What the Spark!? Intro and Use CasesWhat the Spark!? Intro and Use Cases
What the Spark!? Intro and Use Cases
 
Apache NiFi 1.0 in Nutshell
Apache NiFi 1.0 in NutshellApache NiFi 1.0 in Nutshell
Apache NiFi 1.0 in Nutshell
 
Togaf introduction and core concepts
Togaf introduction and core conceptsTogaf introduction and core concepts
Togaf introduction and core concepts
 
Apache Hadoop YARN
Apache Hadoop YARNApache Hadoop YARN
Apache Hadoop YARN
 
TOGAF 9 Architectural Artifacts
TOGAF 9  Architectural ArtifactsTOGAF 9  Architectural Artifacts
TOGAF 9 Architectural Artifacts
 
TOGAF Complete Slide Deck
TOGAF Complete Slide DeckTOGAF Complete Slide Deck
TOGAF Complete Slide Deck
 
Hiveを高速化するLLAP
Hiveを高速化するLLAPHiveを高速化するLLAP
Hiveを高速化するLLAP
 
Building large scale applications in yarn with apache twill
Building large scale applications in yarn with apache twillBuilding large scale applications in yarn with apache twill
Building large scale applications in yarn with apache twill
 
Harnessing the power of YARN with Apache Twill
Harnessing the power of YARN with Apache TwillHarnessing the power of YARN with Apache Twill
Harnessing the power of YARN with Apache Twill
 
Apache Hadoop YARN, NameNode HA, HDFS Federation
Apache Hadoop YARN, NameNode HA, HDFS FederationApache Hadoop YARN, NameNode HA, HDFS Federation
Apache Hadoop YARN, NameNode HA, HDFS Federation
 
Hadoop Summit Tokyo HDP Sandbox Workshop
Hadoop Summit Tokyo HDP Sandbox Workshop Hadoop Summit Tokyo HDP Sandbox Workshop
Hadoop Summit Tokyo HDP Sandbox Workshop
 
Hortonworks Data In Motion Series Part 3 - HDF Ambari
Hortonworks Data In Motion Series Part 3 - HDF Ambari Hortonworks Data In Motion Series Part 3 - HDF Ambari
Hortonworks Data In Motion Series Part 3 - HDF Ambari
 
Learn Togaf 9.1 in 100 slides!
Learn Togaf 9.1 in 100 slides!Learn Togaf 9.1 in 100 slides!
Learn Togaf 9.1 in 100 slides!
 
Real-Time Data Flows with Apache NiFi
Real-Time Data Flows with Apache NiFiReal-Time Data Flows with Apache NiFi
Real-Time Data Flows with Apache NiFi
 

Similar to Intro to Spark & Zeppelin - Crash Course - HS16SJ

Crash Course HS16Melb - Hands on Intro to Spark & Zeppelin
Crash Course HS16Melb - Hands on Intro to Spark & Zeppelin Crash Course HS16Melb - Hands on Intro to Spark & Zeppelin
Crash Course HS16Melb - Hands on Intro to Spark & Zeppelin DataWorks Summit/Hadoop Summit
 
Accelerate Big Data Processing with High-Performance Computing Technologies
Accelerate Big Data Processing with High-Performance Computing TechnologiesAccelerate Big Data Processing with High-Performance Computing Technologies
Accelerate Big Data Processing with High-Performance Computing TechnologiesIntel® Software
 
Intro to Spark with Zeppelin
Intro to Spark with ZeppelinIntro to Spark with Zeppelin
Intro to Spark with ZeppelinHortonworks
 
Paris FOD Meetup #5 Hortonworks Presentation
Paris FOD Meetup #5 Hortonworks PresentationParis FOD Meetup #5 Hortonworks Presentation
Paris FOD Meetup #5 Hortonworks PresentationAbdelkrim Hadjidj
 
Apache Spark: Lightning Fast Cluster Computing
Apache Spark: Lightning Fast Cluster ComputingApache Spark: Lightning Fast Cluster Computing
Apache Spark: Lightning Fast Cluster ComputingAll Things Open
 
The Open Source and Cloud Part of Oracle Big Data Cloud Service for Beginners
The Open Source and Cloud Part of Oracle Big Data Cloud Service for BeginnersThe Open Source and Cloud Part of Oracle Big Data Cloud Service for Beginners
The Open Source and Cloud Part of Oracle Big Data Cloud Service for BeginnersEdelweiss Kammermann
 
PyMADlib - A Python wrapper for MADlib : in-database, parallel, machine learn...
PyMADlib - A Python wrapper for MADlib : in-database, parallel, machine learn...PyMADlib - A Python wrapper for MADlib : in-database, parallel, machine learn...
PyMADlib - A Python wrapper for MADlib : in-database, parallel, machine learn...Srivatsan Ramanujam
 
2016 August POWER Up Your Insights - IBM System Summit Mumbai
2016 August POWER Up Your Insights - IBM System Summit Mumbai2016 August POWER Up Your Insights - IBM System Summit Mumbai
2016 August POWER Up Your Insights - IBM System Summit MumbaiAnand Haridass
 
Arun Rathinasabapathy, Senior Software Engineer, LexisNexis at MLconf ATL 2016
Arun Rathinasabapathy, Senior Software Engineer, LexisNexis at MLconf ATL 2016Arun Rathinasabapathy, Senior Software Engineer, LexisNexis at MLconf ATL 2016
Arun Rathinasabapathy, Senior Software Engineer, LexisNexis at MLconf ATL 2016MLconf
 
Java One 2017: Open Source Big Data in the Cloud: Hadoop, M/R, Hive, Spark an...
Java One 2017: Open Source Big Data in the Cloud: Hadoop, M/R, Hive, Spark an...Java One 2017: Open Source Big Data in the Cloud: Hadoop, M/R, Hive, Spark an...
Java One 2017: Open Source Big Data in the Cloud: Hadoop, M/R, Hive, Spark an...Frank Munz
 
Apache Hadoop 3.0 Community Update
Apache Hadoop 3.0 Community UpdateApache Hadoop 3.0 Community Update
Apache Hadoop 3.0 Community UpdateDataWorks Summit
 
Meetup Oracle Database MAD: 2.1 Data Management Trends: SQL, NoSQL y Big Data
Meetup Oracle Database MAD: 2.1 Data Management Trends: SQL, NoSQL y Big Data Meetup Oracle Database MAD: 2.1 Data Management Trends: SQL, NoSQL y Big Data
Meetup Oracle Database MAD: 2.1 Data Management Trends: SQL, NoSQL y Big Data avanttic Consultoría Tecnológica
 
Whats new in Oracle Database 12c release 12.1.0.2
Whats new in Oracle Database 12c release 12.1.0.2Whats new in Oracle Database 12c release 12.1.0.2
Whats new in Oracle Database 12c release 12.1.0.2Connor McDonald
 
Webinar: Large Scale Graph Processing with IBM Power Systems & Neo4j
Webinar: Large Scale Graph Processing with IBM Power Systems & Neo4jWebinar: Large Scale Graph Processing with IBM Power Systems & Neo4j
Webinar: Large Scale Graph Processing with IBM Power Systems & Neo4jNeo4j
 
Improving Hadoop Resiliency and Operational Efficiency with EMC Isilon
Improving Hadoop Resiliency and Operational Efficiency with EMC IsilonImproving Hadoop Resiliency and Operational Efficiency with EMC Isilon
Improving Hadoop Resiliency and Operational Efficiency with EMC IsilonDataWorks Summit/Hadoop Summit
 
Tiny Batches, in the wine: Shiny New Bits in Spark Streaming
Tiny Batches, in the wine: Shiny New Bits in Spark StreamingTiny Batches, in the wine: Shiny New Bits in Spark Streaming
Tiny Batches, in the wine: Shiny New Bits in Spark StreamingPaco Nathan
 
Data core overview - haluk-final
Data core overview - haluk-finalData core overview - haluk-final
Data core overview - haluk-finalHaluk Ulubay
 

Similar to Intro to Spark & Zeppelin - Crash Course - HS16SJ (20)

Apache Spark Crash Course
Apache Spark Crash CourseApache Spark Crash Course
Apache Spark Crash Course
 
Crash Course HS16Melb - Hands on Intro to Spark & Zeppelin
Crash Course HS16Melb - Hands on Intro to Spark & Zeppelin Crash Course HS16Melb - Hands on Intro to Spark & Zeppelin
Crash Course HS16Melb - Hands on Intro to Spark & Zeppelin
 
Accelerate Big Data Processing with High-Performance Computing Technologies
Accelerate Big Data Processing with High-Performance Computing TechnologiesAccelerate Big Data Processing with High-Performance Computing Technologies
Accelerate Big Data Processing with High-Performance Computing Technologies
 
Intro to Spark with Zeppelin
Intro to Spark with ZeppelinIntro to Spark with Zeppelin
Intro to Spark with Zeppelin
 
Paris FOD Meetup #5 Hortonworks Presentation
Paris FOD Meetup #5 Hortonworks PresentationParis FOD Meetup #5 Hortonworks Presentation
Paris FOD Meetup #5 Hortonworks Presentation
 
Apache Spark: Lightning Fast Cluster Computing
Apache Spark: Lightning Fast Cluster ComputingApache Spark: Lightning Fast Cluster Computing
Apache Spark: Lightning Fast Cluster Computing
 
The Open Source and Cloud Part of Oracle Big Data Cloud Service for Beginners
The Open Source and Cloud Part of Oracle Big Data Cloud Service for BeginnersThe Open Source and Cloud Part of Oracle Big Data Cloud Service for Beginners
The Open Source and Cloud Part of Oracle Big Data Cloud Service for Beginners
 
PyMADlib - A Python wrapper for MADlib : in-database, parallel, machine learn...
PyMADlib - A Python wrapper for MADlib : in-database, parallel, machine learn...PyMADlib - A Python wrapper for MADlib : in-database, parallel, machine learn...
PyMADlib - A Python wrapper for MADlib : in-database, parallel, machine learn...
 
Hadoop 3 in a Nutshell
Hadoop 3 in a NutshellHadoop 3 in a Nutshell
Hadoop 3 in a Nutshell
 
Oracle SPARC T7 a M7 servery
Oracle SPARC T7 a M7 serveryOracle SPARC T7 a M7 servery
Oracle SPARC T7 a M7 servery
 
2016 August POWER Up Your Insights - IBM System Summit Mumbai
2016 August POWER Up Your Insights - IBM System Summit Mumbai2016 August POWER Up Your Insights - IBM System Summit Mumbai
2016 August POWER Up Your Insights - IBM System Summit Mumbai
 
Arun Rathinasabapathy, Senior Software Engineer, LexisNexis at MLconf ATL 2016
Arun Rathinasabapathy, Senior Software Engineer, LexisNexis at MLconf ATL 2016Arun Rathinasabapathy, Senior Software Engineer, LexisNexis at MLconf ATL 2016
Arun Rathinasabapathy, Senior Software Engineer, LexisNexis at MLconf ATL 2016
 
Java One 2017: Open Source Big Data in the Cloud: Hadoop, M/R, Hive, Spark an...
Java One 2017: Open Source Big Data in the Cloud: Hadoop, M/R, Hive, Spark an...Java One 2017: Open Source Big Data in the Cloud: Hadoop, M/R, Hive, Spark an...
Java One 2017: Open Source Big Data in the Cloud: Hadoop, M/R, Hive, Spark an...
 
Apache Hadoop 3.0 Community Update
Apache Hadoop 3.0 Community UpdateApache Hadoop 3.0 Community Update
Apache Hadoop 3.0 Community Update
 
Meetup Oracle Database MAD: 2.1 Data Management Trends: SQL, NoSQL y Big Data
Meetup Oracle Database MAD: 2.1 Data Management Trends: SQL, NoSQL y Big Data Meetup Oracle Database MAD: 2.1 Data Management Trends: SQL, NoSQL y Big Data
Meetup Oracle Database MAD: 2.1 Data Management Trends: SQL, NoSQL y Big Data
 
Whats new in Oracle Database 12c release 12.1.0.2
Whats new in Oracle Database 12c release 12.1.0.2Whats new in Oracle Database 12c release 12.1.0.2
Whats new in Oracle Database 12c release 12.1.0.2
 
Webinar: Large Scale Graph Processing with IBM Power Systems & Neo4j
Webinar: Large Scale Graph Processing with IBM Power Systems & Neo4jWebinar: Large Scale Graph Processing with IBM Power Systems & Neo4j
Webinar: Large Scale Graph Processing with IBM Power Systems & Neo4j
 
Improving Hadoop Resiliency and Operational Efficiency with EMC Isilon
Improving Hadoop Resiliency and Operational Efficiency with EMC IsilonImproving Hadoop Resiliency and Operational Efficiency with EMC Isilon
Improving Hadoop Resiliency and Operational Efficiency with EMC Isilon
 
Tiny Batches, in the wine: Shiny New Bits in Spark Streaming
Tiny Batches, in the wine: Shiny New Bits in Spark StreamingTiny Batches, in the wine: Shiny New Bits in Spark Streaming
Tiny Batches, in the wine: Shiny New Bits in Spark Streaming
 
Data core overview - haluk-final
Data core overview - haluk-finalData core overview - haluk-final
Data core overview - haluk-final
 

More from DataWorks Summit/Hadoop Summit

Unleashing the Power of Apache Atlas with Apache Ranger
Unleashing the Power of Apache Atlas with Apache RangerUnleashing the Power of Apache Atlas with Apache Ranger
Unleashing the Power of Apache Atlas with Apache RangerDataWorks Summit/Hadoop Summit
 
Enabling Digital Diagnostics with a Data Science Platform
Enabling Digital Diagnostics with a Data Science PlatformEnabling Digital Diagnostics with a Data Science Platform
Enabling Digital Diagnostics with a Data Science PlatformDataWorks Summit/Hadoop Summit
 
Double Your Hadoop Performance with Hortonworks SmartSense
Double Your Hadoop Performance with Hortonworks SmartSenseDouble Your Hadoop Performance with Hortonworks SmartSense
Double Your Hadoop Performance with Hortonworks SmartSenseDataWorks Summit/Hadoop Summit
 
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...DataWorks Summit/Hadoop Summit
 
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...DataWorks Summit/Hadoop Summit
 
Mool - Automated Log Analysis using Data Science and ML
Mool - Automated Log Analysis using Data Science and MLMool - Automated Log Analysis using Data Science and ML
Mool - Automated Log Analysis using Data Science and MLDataWorks Summit/Hadoop Summit
 
The Challenge of Driving Business Value from the Analytics of Things (AOT)
The Challenge of Driving Business Value from the Analytics of Things (AOT)The Challenge of Driving Business Value from the Analytics of Things (AOT)
The Challenge of Driving Business Value from the Analytics of Things (AOT)DataWorks Summit/Hadoop Summit
 
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...DataWorks Summit/Hadoop Summit
 
Scaling HDFS to Manage Billions of Files with Distributed Storage Schemes
Scaling HDFS to Manage Billions of Files with Distributed Storage SchemesScaling HDFS to Manage Billions of Files with Distributed Storage Schemes
Scaling HDFS to Manage Billions of Files with Distributed Storage SchemesDataWorks Summit/Hadoop Summit
 

More from DataWorks Summit/Hadoop Summit (20)

Running Apache Spark & Apache Zeppelin in Production
Running Apache Spark & Apache Zeppelin in ProductionRunning Apache Spark & Apache Zeppelin in Production
Running Apache Spark & Apache Zeppelin in Production
 
State of Security: Apache Spark & Apache Zeppelin
State of Security: Apache Spark & Apache ZeppelinState of Security: Apache Spark & Apache Zeppelin
State of Security: Apache Spark & Apache Zeppelin
 
Unleashing the Power of Apache Atlas with Apache Ranger
Unleashing the Power of Apache Atlas with Apache RangerUnleashing the Power of Apache Atlas with Apache Ranger
Unleashing the Power of Apache Atlas with Apache Ranger
 
Enabling Digital Diagnostics with a Data Science Platform
Enabling Digital Diagnostics with a Data Science PlatformEnabling Digital Diagnostics with a Data Science Platform
Enabling Digital Diagnostics with a Data Science Platform
 
Revolutionize Text Mining with Spark and Zeppelin
Revolutionize Text Mining with Spark and ZeppelinRevolutionize Text Mining with Spark and Zeppelin
Revolutionize Text Mining with Spark and Zeppelin
 
Double Your Hadoop Performance with Hortonworks SmartSense
Double Your Hadoop Performance with Hortonworks SmartSenseDouble Your Hadoop Performance with Hortonworks SmartSense
Double Your Hadoop Performance with Hortonworks SmartSense
 
Hadoop Crash Course
Hadoop Crash CourseHadoop Crash Course
Hadoop Crash Course
 
Data Science Crash Course
Data Science Crash CourseData Science Crash Course
Data Science Crash Course
 
Apache Spark Crash Course
Apache Spark Crash CourseApache Spark Crash Course
Apache Spark Crash Course
 
Dataflow with Apache NiFi
Dataflow with Apache NiFiDataflow with Apache NiFi
Dataflow with Apache NiFi
 
Schema Registry - Set you Data Free
Schema Registry - Set you Data FreeSchema Registry - Set you Data Free
Schema Registry - Set you Data Free
 
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
Building a Large-Scale, Adaptive Recommendation Engine with Apache Flink and ...
 
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
Real-Time Anomaly Detection using LSTM Auto-Encoders with Deep Learning4J on ...
 
Mool - Automated Log Analysis using Data Science and ML
Mool - Automated Log Analysis using Data Science and MLMool - Automated Log Analysis using Data Science and ML
Mool - Automated Log Analysis using Data Science and ML
 
HBase in Practice
HBase in Practice HBase in Practice
HBase in Practice
 
The Challenge of Driving Business Value from the Analytics of Things (AOT)
The Challenge of Driving Business Value from the Analytics of Things (AOT)The Challenge of Driving Business Value from the Analytics of Things (AOT)
The Challenge of Driving Business Value from the Analytics of Things (AOT)
 
Breaking the 1 Million OPS/SEC Barrier in HOPS Hadoop
Breaking the 1 Million OPS/SEC Barrier in HOPS HadoopBreaking the 1 Million OPS/SEC Barrier in HOPS Hadoop
Breaking the 1 Million OPS/SEC Barrier in HOPS Hadoop
 
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
From Regulatory Process Verification to Predictive Maintenance and Beyond wit...
 
Backup and Disaster Recovery in Hadoop
Backup and Disaster Recovery in Hadoop Backup and Disaster Recovery in Hadoop
Backup and Disaster Recovery in Hadoop
 
Scaling HDFS to Manage Billions of Files with Distributed Storage Schemes
Scaling HDFS to Manage Billions of Files with Distributed Storage SchemesScaling HDFS to Manage Billions of Files with Distributed Storage Schemes
Scaling HDFS to Manage Billions of Files with Distributed Storage Schemes
 

Recently uploaded

NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopBachir Benyammi
 
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxBuilding AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxUdaiappa Ramachandran
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Brian Pichman
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfAijun Zhang
 
Computer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsComputer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsSeth Reyes
 
20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-pyJamie (Taka) Wang
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1DianaGray10
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintMahmoud Rabie
 
9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding TeamAdam Moalla
 
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...UbiTrack UK
 
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXVoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXTarek Kalaji
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfDaniel Santiago Silva Capera
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Will Schroeder
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdfPedro Manuel
 
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostKubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostMatt Ray
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesDavid Newbury
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6DianaGray10
 
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaborationbruanjhuli
 

Recently uploaded (20)

NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 Workshop
 
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxBuilding AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptx
 
Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )Building Your Own AI Instance (TBLC AI )
Building Your Own AI Instance (TBLC AI )
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdf
 
Computer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and HazardsComputer 10: Lesson 10 - Online Crimes and Hazards
Computer 10: Lesson 10 - Online Crimes and Hazards
 
20230202 - Introduction to tis-py
20230202 - Introduction to tis-py20230202 - Introduction to tis-py
20230202 - Introduction to tis-py
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
 
Empowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership BlueprintEmpowering Africa's Next Generation: The AI Leadership Blueprint
Empowering Africa's Next Generation: The AI Leadership Blueprint
 
9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team9 Steps For Building Winning Founding Team
9 Steps For Building Winning Founding Team
 
20150722 - AGV
20150722 - AGV20150722 - AGV
20150722 - AGV
 
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
 
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXVoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBX
 
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdfIaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
IaC & GitOps in a Nutshell - a FridayInANuthshell Episode.pdf
 
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
Apres-Cyber - The Data Dilemma: Bridging Offensive Operations and Machine Lea...
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdf
 
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostKubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
 
20230104 - machine vision
20230104 - machine vision20230104 - machine vision
20230104 - machine vision
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond Ontologies
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
 
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online CollaborationCOMPUTER 10: Lesson 7 - File Storage and Online Collaboration
COMPUTER 10: Lesson 7 - File Storage and Online Collaboration
 

Intro to Spark & Zeppelin - Crash Course - HS16SJ