Personal Information
Organização/Local de trabalho
San Francisco Bay Area, CA United States
Cargo
Data Expert with System Architecture Insight
Setor
Technology / Software / Internet
Sobre
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...
Marcadores
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
Ver mais
Apresentações
(4)Gostaram
(67)Intuit's Data Mesh - Data Mesh Leaning Community meetup 5.13.2021
Tristan Baker
•
Há 2 anos
Spark SQL Bucketing at Facebook
Databricks
•
Há 4 anos
Modernizing Big Data Workload Using Amazon EMR & AWS Glue
Noritaka Sekiyama
•
Há 4 anos
How to test infrastructure code: automated testing for Terraform, Kubernetes, Docker, Packer and more
Yevgeniy Brikman
•
Há 4 anos
Presto Strata London 2019: Cost-Based Optimizer for interactive SQL on anything
Piotr Findeisen
•
Há 5 anos
Trillion Dollar Coach Book (Bill Campbell)
Eric Schmidt
•
Há 5 anos
"Smooth Operator" [Bay Area NewSQL meetup]
Kevin Xu
•
Há 5 anos
Dynamic pricing of Lyft rides using streaming
Amar Pai
•
Há 5 anos
YugaByte DB Internals - Storage Engine and Transactions
Yugabyte
•
Há 5 anos
What’s new in Apache Spark 2.3
DataWorks Summit
•
Há 5 anos
ORC improvement in Apache Spark 2.3
DataWorks Summit
•
Há 6 anos
Using Apache Arrow, Calcite, and Parquet to Build a Relational Cache
Dremio Corporation
•
Há 6 anos
Using Apache Arrow, Calcite, and Parquet to Build a Relational Cache
Dremio Corporation
•
Há 6 anos
Apache Arrow: In Theory, In Practice
Dremio Corporation
•
Há 6 anos
Top 5 Deep Learning and AI Stories - October 6, 2017
NVIDIA
•
Há 6 anos
Deep Dive into Project Tungsten: Bringing Spark Closer to Bare Metal-(Josh Rosen, Databricks)
Spark Summit
•
Há 8 anos
Handling Data Skew Adaptively In Spark Using Dynamic Repartitioning
Spark Summit
•
Há 7 anos
Scala Reflection & Runtime MetaProgramming
Meir Maor
•
Há 7 anos
What to Expect for Big Data and Apache Spark in 2017
Databricks
•
Há 7 anos
Hive: Loading Data
Benjamin Leonhardi
•
Há 8 anos
Tuning Java for Big Data
Scott Seighman
•
Há 9 anos
Deep Dive Into Catalyst: Apache Spark 2.0'S Optimizer
Spark Summit
•
Há 7 anos
Introducing Neo4j 3.0
Neo4j
•
Há 8 anos
File Format Benchmark - Avro, JSON, ORC & Parquet
DataWorks Summit/Hadoop Summit
•
Há 7 anos
Dongwon Kim – A Comparative Performance Evaluation of Flink
Flink Forward
•
Há 8 anos
Why apache Flink is the 4G of Big Data Analytics Frameworks
Slim Baltagi
•
Há 8 anos
Apache Hive Hook
Minwoo Kim
•
Há 10 anos
Spark etl
Imran Rashid
•
Há 8 anos
Hive tuning
Michael Zhang
•
Há 10 anos
Personal Information
Organização/Local de trabalho
San Francisco Bay Area, CA United States
Cargo
Data Expert with System Architecture Insight
Setor
Technology / Software / Internet
Sobre
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...
Marcadores
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
Ver mais