Personal Information
Entreprise/Lieu de travail
San Francisco Bay Area, CA United States
Profession
Data Expert with System Architecture Insight
Secteur d’activité
Technology / Software / Internet
Site Web
goldenorbit.wordpress.com
À propos
With the thorough understandings of data, application & network architecture, Eric has developed & proven a set of approaches to improve the performance & ROI by 50%~200% based on the company's existing DW/BI infrastructure.
His 1st philosophy is to make the best use of the tools and to create better tools, as he has witnessed many poor project results simply because everyone expects the out-of-box features to satisfy all the requirements, yet few are willing to to deep dive into the tool and explore its full potential.
We often debates about which tool is the best, yet Eric believes that it is crucial to provide the valuable consulting and eduction to enable more team members and clien...
Mots-clés
hadoop
incremental
upsert
time travel
data warehouse
hive
hudi
delta
iceberg
data lake
big data
json
etl
nosql
sql
elt
jdbc
fastload
mapreduce
tdch
teradata
Tout plus
Présentations
(4)J’aime
(67)Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021
Tristan Baker
•
il y a 2 ans
Spark SQL Bucketing at Facebook
Databricks
•
il y a 4 ans
Modernizing Big Data Workload Using Amazon EMR & AWS Glue
Noritaka Sekiyama
•
il y a 4 ans
How to test infrastructure code: automated testing for Terraform, Kubernetes, Docker, Packer and more
Yevgeniy Brikman
•
il y a 4 ans
Presto Strata London 2019: Cost-Based Optimizer for interactive SQL on anything
Piotr Findeisen
•
il y a 5 ans
Trillion Dollar Coach Book (Bill Campbell)
Eric Schmidt
•
il y a 5 ans
"Smooth Operator" [Bay Area NewSQL meetup]
Kevin Xu
•
il y a 5 ans
Dynamic pricing of Lyft rides using streaming
Amar Pai
•
il y a 5 ans
YugaByte DB Internals - Storage Engine and Transactions
Yugabyte
•
il y a 6 ans
What’s new in Apache Spark 2.3
DataWorks Summit
•
il y a 5 ans
ORC improvement in Apache Spark 2.3
DataWorks Summit
•
il y a 6 ans
Using Apache Arrow, Calcite, and Parquet to Build a Relational Cache
Dremio Corporation
•
il y a 6 ans
Using Apache Arrow, Calcite, and Parquet to Build a Relational Cache
Dremio Corporation
•
il y a 6 ans
Apache Arrow: In Theory, In Practice
Dremio Corporation
•
il y a 6 ans
What is Artificial Intelligence | Artificial Intelligence Tutorial For Beginners | Edureka
Edureka!
•
il y a 6 ans
Top 5 Deep Learning and AI Stories - October 6, 2017
NVIDIA
•
il y a 6 ans
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Rosen, Databricks)
Spark Summit
•
il y a 8 ans
Handling Data Skew Adaptively In Spark Using Dynamic Repartitioning
Spark Summit
•
il y a 7 ans
Scala Reflection & Runtime MetaProgramming
Meir Maor
•
il y a 8 ans
What to Expect for Big Data and Apache Spark in 2017
Databricks
•
il y a 7 ans
Hive: Loading Data
Benjamin Leonhardi
•
il y a 8 ans
Tuning Java for Big Data
Scott Seighman
•
il y a 9 ans
Deep Dive Into Catalyst: Apache Spark 2.0'S Optimizer
Spark Summit
•
il y a 7 ans
Introducing Neo4j 3.0
Neo4j
•
il y a 8 ans
File Format Benchmark - Avro, JSON, ORC & Parquet
DataWorks Summit/Hadoop Summit
•
il y a 7 ans
Dongwon Kim – A Comparative Performance Evaluation of Flink
Flink Forward
•
il y a 8 ans
Why apache Flink is the 4G of Big Data Analytics Frameworks
Slim Baltagi
•
il y a 8 ans
Apache Hive Hook
Minwoo Kim
•
il y a 10 ans
Spark etl
Imran Rashid
•
il y a 8 ans
Hive tuning
Michael Zhang
•
il y a 10 ans
Personal Information
Entreprise/Lieu de travail
San Francisco Bay Area, CA United States
Profession
Data Expert with System Architecture Insight
Secteur d’activité
Technology / Software / Internet
Site Web
goldenorbit.wordpress.com
À propos
With the thorough understandings of data, application & network architecture, Eric has developed & proven a set of approaches to improve the performance & ROI by 50%~200% based on the company's existing DW/BI infrastructure.
His 1st philosophy is to make the best use of the tools and to create better tools, as he has witnessed many poor project results simply because everyone expects the out-of-box features to satisfy all the requirements, yet few are willing to to deep dive into the tool and explore its full potential.
We often debates about which tool is the best, yet Eric believes that it is crucial to provide the valuable consulting and eduction to enable more team members and clien...
Mots-clés
hadoop
incremental
upsert
time travel
data warehouse
hive
hudi
delta
iceberg
data lake
big data
json
etl
nosql
sql
elt
jdbc
fastload
mapreduce
tdch
teradata
Tout plus