SlideShare a Scribd company logo
Serial-war
Xuechao Wu
Evaluate the performance of serialization formats
Insight Data Engineering Fellowship, SV
Ideas and Motivations
• What format should be used for real-time apps?
• Bandwidth usage
DEMO
www.serialwar.xyz
PIPELINE
Serialization Deserialization Dashboard
Ingestion Processing Cache
PIPELINE
m4.x
m4.x m4.x
m4.x m4.x
m4.x
m4.x
$1.673/hr
Protocol Buffers
33 Bytes
*https://martin.kleppmann.com/2012/12/05/schema-ev olution- in-avr o-pr otocol- buffers-thrift.html
Apache Avro
32 Bytes
*https://martin.kleppmann.com/2012/12/05/schema-ev olution- in-avr o-pr otocol- buffers-thrift.html
AverageByKey
latency_stream = message_DStream.
map(lambda x:json.loads(x)). //x:{json}
map(lambda x:(math.ceil(time.time()),time.time()-x["time"])). //(key_time,latency)
combineByKey(lambda value: (value, 1),lambda x, value: (x[0] + value, x[1] + 1),lambda x, y: (x[0] +
y[0], x[1] + y[1])). //(key_time, (value,1)) -> (key_time,(sum,count)) -> (key_time,(sum,count))
map(lambda (label, (value_sum, count)): (label, value_sum / count)) //(time,averaged_latency)
Throughput monitoring
● “peak” pattern
Overall Performance: 2000 events/sec
JSON
~50% more
~34% less latency
Avro
100kb/s
38ms
Protobuf
10% more
17% higher
latency
I would recommend…
JSON
If your app is
Lag-critical
Light-sized data
Avro
If your app is
Data-heavy
real-time critical
Protobuf
If your app is
Heavily
replying on
Google
Services
Need Perfect
documentatio
n
About me
• University of Southern California
• MS Electrical Engineering
Before Insight At Insight
Basic MapReduce Spark, Kafka, Redis
Compression Serialization
Linux C AWS, Bash, tmux…
Basic front-end Full Stack Dev
Think Alone Communication
Avro vs. Protobuf
• Why Avro serialization is slightly smaller than Protobuf?
• Avro schema has both attribution name and type.
• Protobuf tags each record with name tag and type. (1 byte more per record)
• Schema Evolution?
• Avro must keep the most recent version(order matters, field matters), or runtime risk
• Protobuf may decode with previous schema without runtime error, overall more flexible.
• Optional Feature?
• Protobuf: decode with validation for required
• Avro: null in a union to indicate optional

More Related Content

What's hot

DISTRIBUTED PERFORMANCE ANALYSIS USING INFLUXDB AND THE LINUX EBPF VIRTUAL MA...
DISTRIBUTED PERFORMANCE ANALYSIS USING INFLUXDB AND THE LINUX EBPF VIRTUAL MA...DISTRIBUTED PERFORMANCE ANALYSIS USING INFLUXDB AND THE LINUX EBPF VIRTUAL MA...
DISTRIBUTED PERFORMANCE ANALYSIS USING INFLUXDB AND THE LINUX EBPF VIRTUAL MA...
InfluxData
 
InfluxDB & Kubernetes
InfluxDB & KubernetesInfluxDB & Kubernetes
InfluxDB & Kubernetes
InfluxData
 
eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, I...
eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, I...eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, I...
eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, I...
InfluxData
 
How to build analytics for 100bn logs a month with ClickHouse. By Vadim Tkach...
How to build analytics for 100bn logs a month with ClickHouse. By Vadim Tkach...How to build analytics for 100bn logs a month with ClickHouse. By Vadim Tkach...
How to build analytics for 100bn logs a month with ClickHouse. By Vadim Tkach...
Valery Tkachenko
 
Graphite & Metrictank - Meetup Tel Aviv Yafo
Graphite & Metrictank - Meetup Tel Aviv YafoGraphite & Metrictank - Meetup Tel Aviv Yafo
Graphite & Metrictank - Meetup Tel Aviv Yafo
Dieter Plaetinck
 
How to Measure Latency
How to Measure LatencyHow to Measure Latency
How to Measure Latency
ScyllaDB
 
Exploring the Programming Models for the LUMI Supercomputer
Exploring the Programming Models for the LUMI Supercomputer Exploring the Programming Models for the LUMI Supercomputer
Exploring the Programming Models for the LUMI Supercomputer
George Markomanolis
 
ClickHouse new features and development roadmap, by Aleksei Milovidov
ClickHouse new features and development roadmap, by Aleksei MilovidovClickHouse new features and development roadmap, by Aleksei Milovidov
ClickHouse new features and development roadmap, by Aleksei Milovidov
Altinity Ltd
 
Efficient and Fast Time Series Storage - The missing link in dynamic software...
Efficient and Fast Time Series Storage - The missing link in dynamic software...Efficient and Fast Time Series Storage - The missing link in dynamic software...
Efficient and Fast Time Series Storage - The missing link in dynamic software...
Florian Lautenschlager
 
Adventures in Observability: How in-house ClickHouse deployment enabled Inst...
 Adventures in Observability: How in-house ClickHouse deployment enabled Inst... Adventures in Observability: How in-house ClickHouse deployment enabled Inst...
Adventures in Observability: How in-house ClickHouse deployment enabled Inst...
Altinity Ltd
 
Service Discovery in Prometheus
Service Discovery in PrometheusService Discovery in Prometheus
Service Discovery in Prometheus
Oliver Moser
 
Shipping Data from Postgres to Clickhouse, by Murat Kabilov, Adjust
Shipping Data from Postgres to Clickhouse, by Murat Kabilov, AdjustShipping Data from Postgres to Clickhouse, by Murat Kabilov, Adjust
Shipping Data from Postgres to Clickhouse, by Murat Kabilov, Adjust
Altinity Ltd
 
Influx/Days 2017 San Francisco | Dan Cech
Influx/Days 2017 San Francisco | Dan Cech Influx/Days 2017 San Francisco | Dan Cech
Influx/Days 2017 San Francisco | Dan Cech
InfluxData
 
Utilizing AMD GPUs: Tuning, programming models, and roadmap
Utilizing AMD GPUs: Tuning, programming models, and roadmapUtilizing AMD GPUs: Tuning, programming models, and roadmap
Utilizing AMD GPUs: Tuning, programming models, and roadmap
George Markomanolis
 
Advanced kapacitor
Advanced kapacitorAdvanced kapacitor
Advanced kapacitor
InfluxData
 
ONNC - 0.9.1 release
ONNC - 0.9.1 releaseONNC - 0.9.1 release
ONNC - 0.9.1 release
Luba Tang
 
Getting started with AMD GPUs
Getting started with AMD GPUsGetting started with AMD GPUs
Getting started with AMD GPUs
George Markomanolis
 
Involvement in OpenHPC
Involvement in OpenHPC	Involvement in OpenHPC
Involvement in OpenHPC
Linaro
 
Post-K: Building the Arm HPC Ecosystem
Post-K: Building the Arm HPC Ecosystem	Post-K: Building the Arm HPC Ecosystem
Post-K: Building the Arm HPC Ecosystem
Linaro
 
eBPF Debugging Infrastructure - Current Techniques
eBPF Debugging Infrastructure - Current TechniqueseBPF Debugging Infrastructure - Current Techniques
eBPF Debugging Infrastructure - Current Techniques
Netronome
 

What's hot (20)

DISTRIBUTED PERFORMANCE ANALYSIS USING INFLUXDB AND THE LINUX EBPF VIRTUAL MA...
DISTRIBUTED PERFORMANCE ANALYSIS USING INFLUXDB AND THE LINUX EBPF VIRTUAL MA...DISTRIBUTED PERFORMANCE ANALYSIS USING INFLUXDB AND THE LINUX EBPF VIRTUAL MA...
DISTRIBUTED PERFORMANCE ANALYSIS USING INFLUXDB AND THE LINUX EBPF VIRTUAL MA...
 
InfluxDB & Kubernetes
InfluxDB & KubernetesInfluxDB & Kubernetes
InfluxDB & Kubernetes
 
eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, I...
eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, I...eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, I...
eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, I...
 
How to build analytics for 100bn logs a month with ClickHouse. By Vadim Tkach...
How to build analytics for 100bn logs a month with ClickHouse. By Vadim Tkach...How to build analytics for 100bn logs a month with ClickHouse. By Vadim Tkach...
How to build analytics for 100bn logs a month with ClickHouse. By Vadim Tkach...
 
Graphite & Metrictank - Meetup Tel Aviv Yafo
Graphite & Metrictank - Meetup Tel Aviv YafoGraphite & Metrictank - Meetup Tel Aviv Yafo
Graphite & Metrictank - Meetup Tel Aviv Yafo
 
How to Measure Latency
How to Measure LatencyHow to Measure Latency
How to Measure Latency
 
Exploring the Programming Models for the LUMI Supercomputer
Exploring the Programming Models for the LUMI Supercomputer Exploring the Programming Models for the LUMI Supercomputer
Exploring the Programming Models for the LUMI Supercomputer
 
ClickHouse new features and development roadmap, by Aleksei Milovidov
ClickHouse new features and development roadmap, by Aleksei MilovidovClickHouse new features and development roadmap, by Aleksei Milovidov
ClickHouse new features and development roadmap, by Aleksei Milovidov
 
Efficient and Fast Time Series Storage - The missing link in dynamic software...
Efficient and Fast Time Series Storage - The missing link in dynamic software...Efficient and Fast Time Series Storage - The missing link in dynamic software...
Efficient and Fast Time Series Storage - The missing link in dynamic software...
 
Adventures in Observability: How in-house ClickHouse deployment enabled Inst...
 Adventures in Observability: How in-house ClickHouse deployment enabled Inst... Adventures in Observability: How in-house ClickHouse deployment enabled Inst...
Adventures in Observability: How in-house ClickHouse deployment enabled Inst...
 
Service Discovery in Prometheus
Service Discovery in PrometheusService Discovery in Prometheus
Service Discovery in Prometheus
 
Shipping Data from Postgres to Clickhouse, by Murat Kabilov, Adjust
Shipping Data from Postgres to Clickhouse, by Murat Kabilov, AdjustShipping Data from Postgres to Clickhouse, by Murat Kabilov, Adjust
Shipping Data from Postgres to Clickhouse, by Murat Kabilov, Adjust
 
Influx/Days 2017 San Francisco | Dan Cech
Influx/Days 2017 San Francisco | Dan Cech Influx/Days 2017 San Francisco | Dan Cech
Influx/Days 2017 San Francisco | Dan Cech
 
Utilizing AMD GPUs: Tuning, programming models, and roadmap
Utilizing AMD GPUs: Tuning, programming models, and roadmapUtilizing AMD GPUs: Tuning, programming models, and roadmap
Utilizing AMD GPUs: Tuning, programming models, and roadmap
 
Advanced kapacitor
Advanced kapacitorAdvanced kapacitor
Advanced kapacitor
 
ONNC - 0.9.1 release
ONNC - 0.9.1 releaseONNC - 0.9.1 release
ONNC - 0.9.1 release
 
Getting started with AMD GPUs
Getting started with AMD GPUsGetting started with AMD GPUs
Getting started with AMD GPUs
 
Involvement in OpenHPC
Involvement in OpenHPC	Involvement in OpenHPC
Involvement in OpenHPC
 
Post-K: Building the Arm HPC Ecosystem
Post-K: Building the Arm HPC Ecosystem	Post-K: Building the Arm HPC Ecosystem
Post-K: Building the Arm HPC Ecosystem
 
eBPF Debugging Infrastructure - Current Techniques
eBPF Debugging Infrastructure - Current TechniqueseBPF Debugging Infrastructure - Current Techniques
eBPF Debugging Infrastructure - Current Techniques
 

Viewers also liked

Metodosparafijarcreencias 2016
Metodosparafijarcreencias 2016Metodosparafijarcreencias 2016
Metodosparafijarcreencias 2016
amalleret7
 
จิรวัฒน์ นิลสันเทียะ
จิรวัฒน์ นิลสันเทียะจิรวัฒน์ นิลสันเทียะ
จิรวัฒน์ นิลสันเทียะ
ดราย ไอซ์
 
Sophie angus unit 15 witness statement
Sophie angus unit 15   witness statementSophie angus unit 15   witness statement
Sophie angus unit 15 witness statement
sangus7
 
Sophie Angus Unit 15 LO3
Sophie Angus Unit 15 LO3Sophie Angus Unit 15 LO3
Sophie Angus Unit 15 LO3
sangus7
 
Louis vuitton
Louis vuittonLouis vuitton
Louis vuitton
Ankita Biswas
 
Serial-War
Serial-WarSerial-War
Serial-War
Xuechao Wu
 
Marketing Plan for an Android App
Marketing Plan for an Android AppMarketing Plan for an Android App
Marketing Plan for an Android App
Ankita Biswas
 
FN-SEPA-19mai2016-12-LDUMITRU
FN-SEPA-19mai2016-12-LDUMITRUFN-SEPA-19mai2016-12-LDUMITRU
FN-SEPA-19mai2016-12-LDUMITRULucian Dumitru
 
アトラシアン製品概要 (2017年1月現在)
アトラシアン製品概要 (2017年1月現在)アトラシアン製品概要 (2017年1月現在)
アトラシアン製品概要 (2017年1月現在)
アトラシアン株式会社
 
Guidance action plan
Guidance action planGuidance action plan
Guidance action plan
andrelyn diaz
 
Action plan in EsP
Action plan in EsPAction plan in EsP
Action plan in EsP
andrelyn diaz
 

Viewers also liked (11)

Metodosparafijarcreencias 2016
Metodosparafijarcreencias 2016Metodosparafijarcreencias 2016
Metodosparafijarcreencias 2016
 
จิรวัฒน์ นิลสันเทียะ
จิรวัฒน์ นิลสันเทียะจิรวัฒน์ นิลสันเทียะ
จิรวัฒน์ นิลสันเทียะ
 
Sophie angus unit 15 witness statement
Sophie angus unit 15   witness statementSophie angus unit 15   witness statement
Sophie angus unit 15 witness statement
 
Sophie Angus Unit 15 LO3
Sophie Angus Unit 15 LO3Sophie Angus Unit 15 LO3
Sophie Angus Unit 15 LO3
 
Louis vuitton
Louis vuittonLouis vuitton
Louis vuitton
 
Serial-War
Serial-WarSerial-War
Serial-War
 
Marketing Plan for an Android App
Marketing Plan for an Android AppMarketing Plan for an Android App
Marketing Plan for an Android App
 
FN-SEPA-19mai2016-12-LDUMITRU
FN-SEPA-19mai2016-12-LDUMITRUFN-SEPA-19mai2016-12-LDUMITRU
FN-SEPA-19mai2016-12-LDUMITRU
 
アトラシアン製品概要 (2017年1月現在)
アトラシアン製品概要 (2017年1月現在)アトラシアン製品概要 (2017年1月現在)
アトラシアン製品概要 (2017年1月現在)
 
Guidance action plan
Guidance action planGuidance action plan
Guidance action plan
 
Action plan in EsP
Action plan in EsPAction plan in EsP
Action plan in EsP
 

Similar to Xuechao Serial War

Chronix Poster for the Poster Session FAST 2017
Chronix Poster for the Poster Session FAST 2017Chronix Poster for the Poster Session FAST 2017
Chronix Poster for the Poster Session FAST 2017
Florian Lautenschlager
 
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Guido Schmutz
 
Design Patterns for Large-Scale Real-Time Learning
Design Patterns for Large-Scale Real-Time LearningDesign Patterns for Large-Scale Real-Time Learning
Design Patterns for Large-Scale Real-Time Learning
Swiss Big Data User Group
 
End to End Processing of 3.7 Million Telemetry Events per Second using Lambda...
End to End Processing of 3.7 Million Telemetry Events per Second using Lambda...End to End Processing of 3.7 Million Telemetry Events per Second using Lambda...
End to End Processing of 3.7 Million Telemetry Events per Second using Lambda...
DataWorks Summit/Hadoop Summit
 
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Guido Schmutz
 
Cloudera Federal Forum 2014: The Evolution of Machine Learning from Science t...
Cloudera Federal Forum 2014: The Evolution of Machine Learning from Science t...Cloudera Federal Forum 2014: The Evolution of Machine Learning from Science t...
Cloudera Federal Forum 2014: The Evolution of Machine Learning from Science t...
Cloudera, Inc.
 
Ehsan parallel accelerator-dec2015
Ehsan parallel accelerator-dec2015Ehsan parallel accelerator-dec2015
Ehsan parallel accelerator-dec2015
Christian Peel
 
SFBigAnalytics_20190724: Monitor kafka like a Pro
SFBigAnalytics_20190724: Monitor kafka like a ProSFBigAnalytics_20190724: Monitor kafka like a Pro
SFBigAnalytics_20190724: Monitor kafka like a Pro
Chester Chen
 
Realizing the Promise of Portable Data Processing with Apache Beam
Realizing the Promise of Portable Data Processing with Apache BeamRealizing the Promise of Portable Data Processing with Apache Beam
Realizing the Promise of Portable Data Processing with Apache Beam
DataWorks Summit
 
Java Memory Model
Java Memory ModelJava Memory Model
Java Memory Model
Łukasz Koniecki
 
SDAccel Design Contest: Vivado HLS
SDAccel Design Contest: Vivado HLSSDAccel Design Contest: Vivado HLS
SDAccel Design Contest: Vivado HLS
NECST Lab @ Politecnico di Milano
 
The Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open SourceThe Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open Source
DataWorks Summit/Hadoop Summit
 
SC'18 BoF Presentation
SC'18 BoF PresentationSC'18 BoF Presentation
SC'18 BoF Presentation
rcastain
 
The magic behind your Lyft ride prices: A case study on machine learning and ...
The magic behind your Lyft ride prices: A case study on machine learning and ...The magic behind your Lyft ride prices: A case study on machine learning and ...
The magic behind your Lyft ride prices: A case study on machine learning and ...
Karthik Murugesan
 
Containerizing Distributed Pipes
Containerizing Distributed PipesContainerizing Distributed Pipes
Containerizing Distributed Pipes
inside-BigData.com
 
Apache Beam: A unified model for batch and stream processing data
Apache Beam: A unified model for batch and stream processing dataApache Beam: A unified model for batch and stream processing data
Apache Beam: A unified model for batch and stream processing data
DataWorks Summit/Hadoop Summit
 
FleetDB
FleetDBFleetDB
FleetDB
Diego Pacheco
 
ETL with SPARK - First Spark London meetup
ETL with SPARK - First Spark London meetupETL with SPARK - First Spark London meetup
ETL with SPARK - First Spark London meetup
Rafal Kwasny
 
Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...
Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...
Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...
Rafael Ferreira da Silva
 
Apache Beam (incubating)
Apache Beam (incubating)Apache Beam (incubating)
Apache Beam (incubating)
Apache Apex
 

Similar to Xuechao Serial War (20)

Chronix Poster for the Poster Session FAST 2017
Chronix Poster for the Poster Session FAST 2017Chronix Poster for the Poster Session FAST 2017
Chronix Poster for the Poster Session FAST 2017
 
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
 
Design Patterns for Large-Scale Real-Time Learning
Design Patterns for Large-Scale Real-Time LearningDesign Patterns for Large-Scale Real-Time Learning
Design Patterns for Large-Scale Real-Time Learning
 
End to End Processing of 3.7 Million Telemetry Events per Second using Lambda...
End to End Processing of 3.7 Million Telemetry Events per Second using Lambda...End to End Processing of 3.7 Million Telemetry Events per Second using Lambda...
End to End Processing of 3.7 Million Telemetry Events per Second using Lambda...
 
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
Spark (Structured) Streaming vs. Kafka Streams - two stream processing platfo...
 
Cloudera Federal Forum 2014: The Evolution of Machine Learning from Science t...
Cloudera Federal Forum 2014: The Evolution of Machine Learning from Science t...Cloudera Federal Forum 2014: The Evolution of Machine Learning from Science t...
Cloudera Federal Forum 2014: The Evolution of Machine Learning from Science t...
 
Ehsan parallel accelerator-dec2015
Ehsan parallel accelerator-dec2015Ehsan parallel accelerator-dec2015
Ehsan parallel accelerator-dec2015
 
SFBigAnalytics_20190724: Monitor kafka like a Pro
SFBigAnalytics_20190724: Monitor kafka like a ProSFBigAnalytics_20190724: Monitor kafka like a Pro
SFBigAnalytics_20190724: Monitor kafka like a Pro
 
Realizing the Promise of Portable Data Processing with Apache Beam
Realizing the Promise of Portable Data Processing with Apache BeamRealizing the Promise of Portable Data Processing with Apache Beam
Realizing the Promise of Portable Data Processing with Apache Beam
 
Java Memory Model
Java Memory ModelJava Memory Model
Java Memory Model
 
SDAccel Design Contest: Vivado HLS
SDAccel Design Contest: Vivado HLSSDAccel Design Contest: Vivado HLS
SDAccel Design Contest: Vivado HLS
 
The Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open SourceThe Next Generation of Data Processing and Open Source
The Next Generation of Data Processing and Open Source
 
SC'18 BoF Presentation
SC'18 BoF PresentationSC'18 BoF Presentation
SC'18 BoF Presentation
 
The magic behind your Lyft ride prices: A case study on machine learning and ...
The magic behind your Lyft ride prices: A case study on machine learning and ...The magic behind your Lyft ride prices: A case study on machine learning and ...
The magic behind your Lyft ride prices: A case study on machine learning and ...
 
Containerizing Distributed Pipes
Containerizing Distributed PipesContainerizing Distributed Pipes
Containerizing Distributed Pipes
 
Apache Beam: A unified model for batch and stream processing data
Apache Beam: A unified model for batch and stream processing dataApache Beam: A unified model for batch and stream processing data
Apache Beam: A unified model for batch and stream processing data
 
FleetDB
FleetDBFleetDB
FleetDB
 
ETL with SPARK - First Spark London meetup
ETL with SPARK - First Spark London meetupETL with SPARK - First Spark London meetup
ETL with SPARK - First Spark London meetup
 
Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...
Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...
Running Accurate, Scalable, and Reproducible Simulations of Distributed Syste...
 
Apache Beam (incubating)
Apache Beam (incubating)Apache Beam (incubating)
Apache Beam (incubating)
 

Recently uploaded

basic-wireline-operations-course-mahmoud-f-radwan.pdf
basic-wireline-operations-course-mahmoud-f-radwan.pdfbasic-wireline-operations-course-mahmoud-f-radwan.pdf
basic-wireline-operations-course-mahmoud-f-radwan.pdf
NidhalKahouli2
 
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsKuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
Victor Morales
 
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
University of Maribor
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
IJECEIAES
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
MDSABBIROJJAMANPAYEL
 
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
171ticu
 
spirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptxspirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptx
Madan Karki
 
22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt
KrishnaveniKrishnara1
 
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptxML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
JamalHussainArman
 
The Python for beginners. This is an advance computer language.
The Python for beginners. This is an advance computer language.The Python for beginners. This is an advance computer language.
The Python for beginners. This is an advance computer language.
sachin chaurasia
 
A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...
nooriasukmaningtyas
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
co23btech11018
 
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
IJECEIAES
 
Understanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine LearningUnderstanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine Learning
SUTEJAS
 
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball playEric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
enizeyimana36
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
gerogepatton
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Madan Karki
 
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesHarnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Christina Lin
 
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
gerogepatton
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
kandramariana6
 

Recently uploaded (20)

basic-wireline-operations-course-mahmoud-f-radwan.pdf
basic-wireline-operations-course-mahmoud-f-radwan.pdfbasic-wireline-operations-course-mahmoud-f-radwan.pdf
basic-wireline-operations-course-mahmoud-f-radwan.pdf
 
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsKuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
 
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
 
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
 
spirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptxspirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptx
 
22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt22CYT12-Unit-V-E Waste and its Management.ppt
22CYT12-Unit-V-E Waste and its Management.ppt
 
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptxML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
 
The Python for beginners. This is an advance computer language.
The Python for beginners. This is an advance computer language.The Python for beginners. This is an advance computer language.
The Python for beginners. This is an advance computer language.
 
A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
 
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...
 
Understanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine LearningUnderstanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine Learning
 
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball playEric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
 
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesHarnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
 
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
 

Xuechao Serial War