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brief presentation of tokyo cabinet to the Belgian Ruby User group
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Recommandé
tokyo cabinet database overview
Tokyo Cabinet
Tokyo Cabinet
André Mayer
RedHat built a distributed object storage solution named Ceph which first debuted ten years ago. Now we are seeing rapid developments in the industry and we want to take advantage of them. In this talk, we will briefly introduce Ceph, revisit the problems we are seeing when profiling its I/O performance with flash device, and explain why we want to embrace the future by switching to Seastar. We’ll share our experiences with the audience of how and when we are porting our software to this framework.
Scylla Summit 2018: Rebuilding the Ceph Distributed Storage Solution with Sea...
Scylla Summit 2018: Rebuilding the Ceph Distributed Storage Solution with Sea...
ScyllaDB
Ruby,no sql and tokyocabinet
Ruby,no sql and tokyocabinet
biaowei zhuang
Redis - From LAMP to NoSQL (CloudTW meetup-14)
Redis - From LAMP to NoSQL (CloudTW meetup-14)
York Tsai
Join us for a developer workshop where we’ll go hands-on to explore the affinities between Rust, the Tokio framework, and ScyllaDB. You’ll go live with our sample Rust application, built on our new, high performance native Rust client driver.
Build Low-Latency Applications in Rust on ScyllaDB
Build Low-Latency Applications in Rust on ScyllaDB
ScyllaDB
There are two key choices when scaling a NoSQL data store: choosing between a hash or a range based sharding and choosing the right sharding key. Any choice is a trade-off between scalability of read, append, and update workloads. In this talk I will present the standard scaling techniques, some non-universal sharding tricks, less obvious reasons for hotspots, as well as techniques to avoid them.
Avoiding Data Hotspots at Scale
Avoiding Data Hotspots at Scale
ScyllaDB
Type safe, versioned, and rewindable stream processing with Apache {Avro, Kafka} and Scala.
Type safe, versioned, and rewindable stream processing with Apache {Avro, K...
Type safe, versioned, and rewindable stream processing with Apache {Avro, K...
Hisham Mardam-Bey
RedHat built a distributed object storage solution named Ceph which first debuted ten years ago. Now we are seeing rapid developments in the industry and we want to take advantage of them. In this talk, we will briefly introduce Ceph, revisit the problems we are seeing when profiling its I/O performance with flash device, and explain why we want to embrace the future by switching to Seastar. We’ll share our experiences with the audience of how and when we are porting our software to this framework.
Scylla Summit 2018: Rebuilding the Ceph Distributed Storage Solution with Sea...
Scylla Summit 2018: Rebuilding the Ceph Distributed Storage Solution with Sea...
ScyllaDB
Recommandé
tokyo cabinet database overview
Tokyo Cabinet
Tokyo Cabinet
André Mayer
RedHat built a distributed object storage solution named Ceph which first debuted ten years ago. Now we are seeing rapid developments in the industry and we want to take advantage of them. In this talk, we will briefly introduce Ceph, revisit the problems we are seeing when profiling its I/O performance with flash device, and explain why we want to embrace the future by switching to Seastar. We’ll share our experiences with the audience of how and when we are porting our software to this framework.
Scylla Summit 2018: Rebuilding the Ceph Distributed Storage Solution with Sea...
Scylla Summit 2018: Rebuilding the Ceph Distributed Storage Solution with Sea...
ScyllaDB
Ruby,no sql and tokyocabinet
Ruby,no sql and tokyocabinet
biaowei zhuang
Redis - From LAMP to NoSQL (CloudTW meetup-14)
Redis - From LAMP to NoSQL (CloudTW meetup-14)
York Tsai
Join us for a developer workshop where we’ll go hands-on to explore the affinities between Rust, the Tokio framework, and ScyllaDB. You’ll go live with our sample Rust application, built on our new, high performance native Rust client driver.
Build Low-Latency Applications in Rust on ScyllaDB
Build Low-Latency Applications in Rust on ScyllaDB
ScyllaDB
There are two key choices when scaling a NoSQL data store: choosing between a hash or a range based sharding and choosing the right sharding key. Any choice is a trade-off between scalability of read, append, and update workloads. In this talk I will present the standard scaling techniques, some non-universal sharding tricks, less obvious reasons for hotspots, as well as techniques to avoid them.
Avoiding Data Hotspots at Scale
Avoiding Data Hotspots at Scale
ScyllaDB
Type safe, versioned, and rewindable stream processing with Apache {Avro, Kafka} and Scala.
Type safe, versioned, and rewindable stream processing with Apache {Avro, K...
Type safe, versioned, and rewindable stream processing with Apache {Avro, K...
Hisham Mardam-Bey
RedHat built a distributed object storage solution named Ceph which first debuted ten years ago. Now we are seeing rapid developments in the industry and we want to take advantage of them. In this talk, we will briefly introduce Ceph, revisit the problems we are seeing when profiling its I/O performance with flash device, and explain why we want to embrace the future by switching to Seastar. We’ll share our experiences with the audience of how and when we are porting our software to this framework.
Scylla Summit 2018: Rebuilding the Ceph Distributed Storage Solution with Sea...
Scylla Summit 2018: Rebuilding the Ceph Distributed Storage Solution with Sea...
ScyllaDB
Working with Shared Libraries in Perl
Working with Shared Libraries in Perl
Ido Kanner
Update on Crimson, the Seastarized Ceph
Update on Crimson - the Seastarized Ceph - Seastar Summit
Update on Crimson - the Seastarized Ceph - Seastar Summit
ScyllaDB
Gsummit apis-2013
Gsummit apis-2013
Gsummit apis-2013
Gluster.org
System software engineers have long been taught that disks are slow and sequential I/O is key to performance. With SSD drives I/O really got much faster but not simpler. In this brave new world of rocket-speed throughputs an engineer has to distinguish sustained workload from bursts, (still) take care about I/O buffer sizes, account for disks’ internal parallelism and study mixed I/O characteristics in advance. In this talk we will share some key performance measurements of the modern hardware we’re taking at ScyllaDB and our opinion about the implications for the database and system software design.
P99CONF — What We Need to Unlearn About Persistent Storage
P99CONF — What We Need to Unlearn About Persistent Storage
ScyllaDB
A better way to do distcp on hadoop? Use Gobblin!
Distcp gobblin
Distcp gobblin
Vasanth Rajamani
Alluxio Day VI October 12, 2021 https://www.alluxio.io/alluxio-day/ Speaker: Ke Wang, Facebook Zhenyu Song, Princeton University
Improve Presto Architectural Decisions with Shadow Cache
Improve Presto Architectural Decisions with Shadow Cache
Alluxio, Inc.
PXF - A Unified Access Framework for HDFS datasets
PXF BDAM 2016
PXF BDAM 2016
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GlusterFS Presentation @FOSSCOMM2013
GlusterFS Presentation FOSSCOMM2013 HUA, Athens, GR
GlusterFS Presentation FOSSCOMM2013 HUA, Athens, GR
Theophanis Kontogiannis
In file systems, large sequential writes are more beneficial than small random writes, and hence many storage systems implement a log structured file system. In the same way, the cloud favors large objects more than small objects. Cloud providers place throttling limits on PUTs and GETs, and so it takes significantly longer time to upload a bunch of small objects than a large object of the aggregate size. Moreover, there are per-PUT calls associated with uploading smaller objects. In Netflix, a lot of media assets and their relevant metadata is generated and pushed to cloud. We would like to propose a strategy to compact these small objects into larger blobs before uploading them to Cloud. We will discuss how to select relevant smaller objects, and manage the indexing of these objects within the blob along with modification in reads, overwrites and deletes. Finally, we would showcase the potential impact of such a strategy on Netflix assets in terms of cost and performance.
Object Compaction in Cloud for High Yield
Object Compaction in Cloud for High Yield
ScyllaDB
This presentation was given by Doug Judd at BerlinBuzzwords 2010.
Hypertable Berlin Buzzwords
Hypertable Berlin Buzzwords
hypertable
Introduction To MongoDB Slides - Faro Dev Day, 2016
Introduction to mongo db
Introduction to mongo db
Lawrence Mwai
Xephon K is a time series database using Cassandra as main backend. We talk about how to model time series data in Cassandra and compare its throughput with InfluxDB and KairosDB
Xephon K A Time series database with multiple backends
Xephon K A Time series database with multiple backends
University of California, Santa Cruz
mypipe latches onto a MySQL server with binary log replication enabled and allows for the creation of pipes that can consume the replication stream and act on the data (primarily integrated with Apache Kafka). This presentation goes over mypipe's design and usage of Scala, Akka, Kafka, and Avro after which we look at some applications and possible use cases of mypipe in a data pipeline.
mypipe: Buffering and consuming MySQL changes via Kafka
mypipe: Buffering and consuming MySQL changes via Kafka
Hisham Mardam-Bey
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SFScon14: Schrödinger’s elephant: why PostgreSQL can solve all your database ...
SFScon14: Schrödinger’s elephant: why PostgreSQL can solve all your database ...
South Tyrol Free Software Conference
Zero to 1 Billion+ Records: A True Story of Learning & Scaling GameChanger
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MongoDB
In this session we will look over the various ways .NET is collecting memory, tips how to help GC perform better and tools that will save your day. This is a must attend session for those who still do not know how to troubleshoot memory issues. For the rest it is a nice refresh and new look of features in .NET 4.5. As usual there will be lots of demos.
.NET Memory Primer (Martin Kulov)
.NET Memory Primer (Martin Kulov)
ITCamp
Presto is a widely adopted federated SQL engine for federated querying across multiple data sources. With Presto, you can perform ad hoc querying of data in place. For today’s “data hacker”, Presto helps solve challenges around time to discovery and the amount of time it takes to do ad hoc analysis. In Level 101, you’ll get an overview of Presto, including: A high level overview of Presto & most common use cases The problems it solves and why you should use it A live, hands-on demo on getting Presto running on Docker Real world example: How Twitter uses Presto at scale
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Level 101 for Presto: What is PrestoDB?
Ali LeClerc
In this presentation, Paul introduces InfluxDB, a distributed time series database that he open sourced based on the backend infrastructure at Errplane. He talks about why you'd want a database specifically for time series and he covers the API and some of the key features of InfluxDB, including: • Stores metrics (like Graphite) and events (like page views, exceptions, deploys) • No external dependencies (self contained binary) • Fast. Handles many thousands of writes per second on a single node • HTTP API for reading and writing data • SQL-like query language • Distributed to scale out to many machines • Built in aggregate and statistics functions • Built in downsampling
Introduction to InfluxDB, an Open Source Distributed Time Series Database by ...
Introduction to InfluxDB, an Open Source Distributed Time Series Database by ...
Hakka Labs
Data- How Does It Work-
Data- How Does It Work-
Boyang Niu
Hardware once reserved to HPC systems is entering the datacenter. Cyprien will describe an effort to help developers leverage its new capabilities. Its integration to H2O, along with tools like Caffe, is accelerating and making the platform more powerful. #h2ony
Caffe + H2O - By Cyprien noel
Caffe + H2O - By Cyprien noel
Sri Ambati
株式会社ゆめみ社内勉強会201004資料
SSDとTokyoTyrantやMySQLの性能検証
SSDとTokyoTyrantやMySQLの性能検証
勲 國府田
FutureRuby presentation on extending Tokyo Cabinet with Lua extensions. GitHub repo with sample code & extensions: http://bit.ly/wJpeG
Lean & Mean Tokyo Cabinet Recipes (with Lua) - FutureRuby '09
Lean & Mean Tokyo Cabinet Recipes (with Lua) - FutureRuby '09
Ilya Grigorik
Contenu connexe
Tendances
Working with Shared Libraries in Perl
Working with Shared Libraries in Perl
Ido Kanner
Update on Crimson, the Seastarized Ceph
Update on Crimson - the Seastarized Ceph - Seastar Summit
Update on Crimson - the Seastarized Ceph - Seastar Summit
ScyllaDB
Gsummit apis-2013
Gsummit apis-2013
Gsummit apis-2013
Gluster.org
System software engineers have long been taught that disks are slow and sequential I/O is key to performance. With SSD drives I/O really got much faster but not simpler. In this brave new world of rocket-speed throughputs an engineer has to distinguish sustained workload from bursts, (still) take care about I/O buffer sizes, account for disks’ internal parallelism and study mixed I/O characteristics in advance. In this talk we will share some key performance measurements of the modern hardware we’re taking at ScyllaDB and our opinion about the implications for the database and system software design.
P99CONF — What We Need to Unlearn About Persistent Storage
P99CONF — What We Need to Unlearn About Persistent Storage
ScyllaDB
A better way to do distcp on hadoop? Use Gobblin!
Distcp gobblin
Distcp gobblin
Vasanth Rajamani
Alluxio Day VI October 12, 2021 https://www.alluxio.io/alluxio-day/ Speaker: Ke Wang, Facebook Zhenyu Song, Princeton University
Improve Presto Architectural Decisions with Shadow Cache
Improve Presto Architectural Decisions with Shadow Cache
Alluxio, Inc.
PXF - A Unified Access Framework for HDFS datasets
PXF BDAM 2016
PXF BDAM 2016
Shivram Mani
GlusterFS Presentation @FOSSCOMM2013
GlusterFS Presentation FOSSCOMM2013 HUA, Athens, GR
GlusterFS Presentation FOSSCOMM2013 HUA, Athens, GR
Theophanis Kontogiannis
In file systems, large sequential writes are more beneficial than small random writes, and hence many storage systems implement a log structured file system. In the same way, the cloud favors large objects more than small objects. Cloud providers place throttling limits on PUTs and GETs, and so it takes significantly longer time to upload a bunch of small objects than a large object of the aggregate size. Moreover, there are per-PUT calls associated with uploading smaller objects. In Netflix, a lot of media assets and their relevant metadata is generated and pushed to cloud. We would like to propose a strategy to compact these small objects into larger blobs before uploading them to Cloud. We will discuss how to select relevant smaller objects, and manage the indexing of these objects within the blob along with modification in reads, overwrites and deletes. Finally, we would showcase the potential impact of such a strategy on Netflix assets in terms of cost and performance.
Object Compaction in Cloud for High Yield
Object Compaction in Cloud for High Yield
ScyllaDB
This presentation was given by Doug Judd at BerlinBuzzwords 2010.
Hypertable Berlin Buzzwords
Hypertable Berlin Buzzwords
hypertable
Introduction To MongoDB Slides - Faro Dev Day, 2016
Introduction to mongo db
Introduction to mongo db
Lawrence Mwai
Xephon K is a time series database using Cassandra as main backend. We talk about how to model time series data in Cassandra and compare its throughput with InfluxDB and KairosDB
Xephon K A Time series database with multiple backends
Xephon K A Time series database with multiple backends
University of California, Santa Cruz
mypipe latches onto a MySQL server with binary log replication enabled and allows for the creation of pipes that can consume the replication stream and act on the data (primarily integrated with Apache Kafka). This presentation goes over mypipe's design and usage of Scala, Akka, Kafka, and Avro after which we look at some applications and possible use cases of mypipe in a data pipeline.
mypipe: Buffering and consuming MySQL changes via Kafka
mypipe: Buffering and consuming MySQL changes via Kafka
Hisham Mardam-Bey
Talk by Chris Mair during SFScon14: Schrödinger’s elephant: why PostgreSQL can solve all your database needs
SFScon14: Schrödinger’s elephant: why PostgreSQL can solve all your database ...
SFScon14: Schrödinger’s elephant: why PostgreSQL can solve all your database ...
South Tyrol Free Software Conference
Zero to 1 Billion+ Records: A True Story of Learning & Scaling GameChanger
Zero to 1 Billion+ Records: A True Story of Learning & Scaling GameChanger
MongoDB
In this session we will look over the various ways .NET is collecting memory, tips how to help GC perform better and tools that will save your day. This is a must attend session for those who still do not know how to troubleshoot memory issues. For the rest it is a nice refresh and new look of features in .NET 4.5. As usual there will be lots of demos.
.NET Memory Primer (Martin Kulov)
.NET Memory Primer (Martin Kulov)
ITCamp
Presto is a widely adopted federated SQL engine for federated querying across multiple data sources. With Presto, you can perform ad hoc querying of data in place. For today’s “data hacker”, Presto helps solve challenges around time to discovery and the amount of time it takes to do ad hoc analysis. In Level 101, you’ll get an overview of Presto, including: A high level overview of Presto & most common use cases The problems it solves and why you should use it A live, hands-on demo on getting Presto running on Docker Real world example: How Twitter uses Presto at scale
Level 101 for Presto: What is PrestoDB?
Level 101 for Presto: What is PrestoDB?
Ali LeClerc
In this presentation, Paul introduces InfluxDB, a distributed time series database that he open sourced based on the backend infrastructure at Errplane. He talks about why you'd want a database specifically for time series and he covers the API and some of the key features of InfluxDB, including: • Stores metrics (like Graphite) and events (like page views, exceptions, deploys) • No external dependencies (self contained binary) • Fast. Handles many thousands of writes per second on a single node • HTTP API for reading and writing data • SQL-like query language • Distributed to scale out to many machines • Built in aggregate and statistics functions • Built in downsampling
Introduction to InfluxDB, an Open Source Distributed Time Series Database by ...
Introduction to InfluxDB, an Open Source Distributed Time Series Database by ...
Hakka Labs
Data- How Does It Work-
Data- How Does It Work-
Boyang Niu
Hardware once reserved to HPC systems is entering the datacenter. Cyprien will describe an effort to help developers leverage its new capabilities. Its integration to H2O, along with tools like Caffe, is accelerating and making the platform more powerful. #h2ony
Caffe + H2O - By Cyprien noel
Caffe + H2O - By Cyprien noel
Sri Ambati
Tendances
(20)
Working with Shared Libraries in Perl
Working with Shared Libraries in Perl
Update on Crimson - the Seastarized Ceph - Seastar Summit
Update on Crimson - the Seastarized Ceph - Seastar Summit
Gsummit apis-2013
Gsummit apis-2013
P99CONF — What We Need to Unlearn About Persistent Storage
P99CONF — What We Need to Unlearn About Persistent Storage
Distcp gobblin
Distcp gobblin
Improve Presto Architectural Decisions with Shadow Cache
Improve Presto Architectural Decisions with Shadow Cache
PXF BDAM 2016
PXF BDAM 2016
GlusterFS Presentation FOSSCOMM2013 HUA, Athens, GR
GlusterFS Presentation FOSSCOMM2013 HUA, Athens, GR
Object Compaction in Cloud for High Yield
Object Compaction in Cloud for High Yield
Hypertable Berlin Buzzwords
Hypertable Berlin Buzzwords
Introduction to mongo db
Introduction to mongo db
Xephon K A Time series database with multiple backends
Xephon K A Time series database with multiple backends
mypipe: Buffering and consuming MySQL changes via Kafka
mypipe: Buffering and consuming MySQL changes via Kafka
SFScon14: Schrödinger’s elephant: why PostgreSQL can solve all your database ...
SFScon14: Schrödinger’s elephant: why PostgreSQL can solve all your database ...
Zero to 1 Billion+ Records: A True Story of Learning & Scaling GameChanger
Zero to 1 Billion+ Records: A True Story of Learning & Scaling GameChanger
.NET Memory Primer (Martin Kulov)
.NET Memory Primer (Martin Kulov)
Level 101 for Presto: What is PrestoDB?
Level 101 for Presto: What is PrestoDB?
Introduction to InfluxDB, an Open Source Distributed Time Series Database by ...
Introduction to InfluxDB, an Open Source Distributed Time Series Database by ...
Data- How Does It Work-
Data- How Does It Work-
Caffe + H2O - By Cyprien noel
Caffe + H2O - By Cyprien noel
En vedette
株式会社ゆめみ社内勉強会201004資料
SSDとTokyoTyrantやMySQLの性能検証
SSDとTokyoTyrantやMySQLの性能検証
勲 國府田
FutureRuby presentation on extending Tokyo Cabinet with Lua extensions. GitHub repo with sample code & extensions: http://bit.ly/wJpeG
Lean & Mean Tokyo Cabinet Recipes (with Lua) - FutureRuby '09
Lean & Mean Tokyo Cabinet Recipes (with Lua) - FutureRuby '09
Ilya Grigorik
tokyotalk
tokyotalk
Hiroshi Ono
Tokyocabinet
Tokyocabinet
guestf96ccd
First step guide of Tokyo Cabinet & Tokto Tyrant.
Tokyo Cabinet & Tokyo Tyrant
Tokyo Cabinet & Tokyo Tyrant
輝 子安
Tokyo Cabinet is a library of routines for managing a database. The database is a simple data file containing records, each is a pair of a key and a value. Every key and value is serial bytes with variable length. Both binary data and character string can be used as a key and a value. There is neither concept of data tables nor data types. Records are organized in hash table, B+ tree, or fixed-length array.
Introduction to Tokyo Products
Introduction to Tokyo Products
Mikio Hirabayashi
En vedette
(6)
SSDとTokyoTyrantやMySQLの性能検証
SSDとTokyoTyrantやMySQLの性能検証
Lean & Mean Tokyo Cabinet Recipes (with Lua) - FutureRuby '09
Lean & Mean Tokyo Cabinet Recipes (with Lua) - FutureRuby '09
tokyotalk
tokyotalk
Tokyocabinet
Tokyocabinet
Tokyo Cabinet & Tokyo Tyrant
Tokyo Cabinet & Tokyo Tyrant
Introduction to Tokyo Products
Introduction to Tokyo Products
Similaire à Tokyo Cabinet
Introduction to Apache Marmotta, given at ISWC2014 in Riva del Garda.
Apache Marmotta - Introduction
Apache Marmotta - Introduction
Sebastian Schaffert
Redis Introduction and customized framework base on StackExchange.Redis but update to using singleton pattern and JSON Configuration Mapping with Redis Instance Group and Name concept.
Redis tutoring
Redis tutoring
Chen-Tien Tsai
Understanding of Oracle GoldenGate 12c and it's features, typologies, architecture, concepts etc.
Understanding Oracle GoldenGate 12c
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IT Help Desk Inc
An overview of the various Apache Technologies to help you build your own Big Data solution. A talk given at Berlin Buzzwords, in June 2013.
The other Apache technologies your big data solution needs!
The other Apache technologies your big data solution needs!
gagravarr
Apache Hudi is a data lake platform, that provides streaming primitives (upserts/deletes/change streams) on top of data lake storage. Hudi powers very large data lakes at Uber, Robinhood and other companies, while being pre-installed on four major cloud platforms. Hudi supports exactly-once, near real-time data ingestion from Apache Kafka to cloud storage, which is typically used in-place of a S3/HDFS sink connector to gain transactions and mutability. While this approach is scalable and battle-tested, it can only ingest data in mini batches, leading to lower data freshness. In this talk, we introduce a Kafka Connect Sink Connector for Apache Hudi, which writes data straight into Hudi's log format, making the data immediately queryable, while Hudi's table services like indexing, compaction, clustering work behind the scenes, to further re-organize for better query performance.
Streaming Data Lakes using Kafka Connect + Apache Hudi | Vinoth Chandar, Apac...
Streaming Data Lakes using Kafka Connect + Apache Hudi | Vinoth Chandar, Apac...
HostedbyConfluent
Talk about NLP processing on top of Hadoop using Behemoth by Julien of Digital Pebble
Digital Pebble Behemoth
Digital Pebble Behemoth
Steve Loughran
CouchDB: A NoSQL database
CouchDB: A NoSQL database
Rubyc Slides
NoSQL: Why, When, and How
NoSQL: Why, When, and How
BigBlueHat
Cloud Native London talk about the control layer of Hopsworks.ai and our choice of cloud native services. We built our own multi-tenant services as cloud native services, for the most part.
Building Hopsworks, a cloud-native managed feature store for machine learning
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Jim Dowling
Alluxio Community Office Hour Aug 27, 2019 Speakers: Bin Fan Nakkul Sreenivas
Building a Cloud Native Stack with EMR Spark, Alluxio, and S3
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Alluxio, Inc.
An overview of the various Apache Technologies to help you build your own Big Data solution
The other Apache Technologies your Big Data solution needs
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gagravarr
Amazon EMR is a managed Hadoop service that makes it easy for customers to use big data frameworks and applications like Hadoop, Spark, and Presto to analyze data stored in HDFS or on Amazon S3 , Amazon’s highly scalable object storage service. In this webinar, we will introduce the latest release of Amazon EMR. With Amazon EMR release 5.0, customers can now launch the latest versions of popular open source frameworks including Apache Spark 2.0, Hive 2.1, Presto 0.151, Tez 0.8.4, and Apache Hadoop 2.7.2. We will walk through a demo to show you how to deploy a Hadoop environment within minutes. We will cover common use cases and best practices to lower costs using Amazon S3 as your data store and Amazon EC2 Spot Instances, which allow you to bid on space Amazon computing capacity. Learning Objectives: • Describe the new features and updated frameworks in Amazon EMR 5.0 • Learn best practices and real-world applications for Amazon EMR • Understand how to use EC2 Spot pricing to save costs • Explain the advantages of decoupling storage and compute with Amazon S3 as storage layer for EMR workloads
Introducing Amazon EMR Release 5.0 - August 2016 Monthly Webinar Series
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Amazon Web Services
Introduction to Redis and how to use it from Ruby. Talk presented at EuRuKo 2013 Athens and sponsored by teowaki
Fun with Ruby and Redis
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javier ramirez
Running Production CDC Ingestion Pipelines With Balaji Varadarajan and Pritam K Dey | Current 2022 Robinhood’s mission is to democratize finance for all. Data driven decision making is key to achieving this goal. Data needed are hosted in various OLTP databases. Replicating this data near real time in a reliable fashion to data lakehouse powers many critical use cases for the company. In Robinhood, CDC is not only used for ingestion to data-lake but is also being adopted for inter-system message exchanges between different online micro services. . In this talk, we will describe the evolution of change data capture based ingestion in Robinhood not only in terms of the scale of data stored and queries made, but also the use cases that it supports. We will go in-depth into the CDC architecture built around our Kafka ecosystem using open source system Debezium and Apache Hudi. We will cover online inter-system message exchange use-cases along with our experience running this service at scale in Robinhood along with lessons learned.
Running Production CDC Ingestion Pipelines With Balaji Varadarajan and Pritam...
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DneprCiklumEvents
My EuRuKo 2010 talk about how to build your own web framework using existing Rack components.
Building web framework with Rack
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sickill
Building highly efficient data lakes using Apache Hudi (Incubating) Even with the exponential growth in data volumes, ingesting/storing/managing big data remains unstandardized & in-efficient. Data lakes are a common architectural pattern to organize big data and democratize access to the organization. In this talk, we will discuss different aspects of building honest data lake architectures, pin pointing technical challenges and areas of inefficiency. We will then re-architect the data lake using Apache Hudi (Incubating), which provides streaming primitives right on top of big data. We will show how upserts & incremental change streams provided by Hudi help optimize data ingestion and ETL processing. Further, Apache Hudi manages growth, sizes files of the resulting data lake using purely open-source file formats, also providing for optimized query performance & file system listing. We will also provide hands-on tools and guides for trying this out on your own data lake. Speaker: Vinoth Chandar (Uber) Vinoth is Technical Lead at Uber Data Infrastructure Team
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What you need to know about ceph
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Similaire à Tokyo Cabinet
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Apache Marmotta - Introduction
Apache Marmotta - Introduction
Redis tutoring
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Understanding Oracle GoldenGate 12c
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The other Apache technologies your big data solution needs!
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Building Hopsworks, a cloud-native managed feature store for machine learning
Building Hopsworks, a cloud-native managed feature store for machine learning
Building a Cloud Native Stack with EMR Spark, Alluxio, and S3
Building a Cloud Native Stack with EMR Spark, Alluxio, and S3
The other Apache Technologies your Big Data solution needs
The other Apache Technologies your Big Data solution needs
Introducing Amazon EMR Release 5.0 - August 2016 Monthly Webinar Series
Introducing Amazon EMR Release 5.0 - August 2016 Monthly Webinar Series
Fun with Ruby and Redis
Fun with Ruby and Redis
Running Production CDC Ingestion Pipelines With Balaji Varadarajan and Pritam...
Running Production CDC Ingestion Pipelines With Balaji Varadarajan and Pritam...
03 net saturday anton samarskyy ''document oriented databases for the .net pl...
03 net saturday anton samarskyy ''document oriented databases for the .net pl...
Building web framework with Rack
Building web framework with Rack
SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...
SF Big Analytics 20190612: Building highly efficient data lakes using Apache ...
What you need to know about ceph
What you need to know about ceph
Ceph Day Tokyo - Bring Ceph to Enterprise
Ceph Day Tokyo - Bring Ceph to Enterprise
Technology Stack Discussion
Technology Stack Discussion
Plus de ehuard
Talk euroclojure 2017
Euroclojure 2017
Euroclojure 2017
ehuard
Description of the actor model. Which libraries implement it in Ruby? What are the successful actor libraries in other
Ruby goes to Hollywood
Ruby goes to Hollywood
ehuard
exploring the actor concurrency primitives in ruby and pointing out options in other languages.
Ruby hollywood nordic
Ruby hollywood nordic
ehuard
Ruby goes to hollywood
Ruby goes to hollywood
ehuard
Ruby hollywood
Ruby hollywood
ehuard
talk about concurrency in Ruby, different concurrency models, examples from other languages.
Concurrency: Rubies, plural
Concurrency: Rubies, plural
ehuard
Talk about concurrency in Ruby, and comparison with a few languages
Concurrency
Concurrency
ehuard
Concurrency
Concurrency
ehuard
improved version of 12 hours to rate a rails application - modified after feedback from Euruko and ScotRuby. As presented at Railsconf
12 hours to rate a rails application
12 hours to rate a rails application
ehuard
Talk given at Euruko 2010: the talk describes how to quickly evaluate the quality of a Rails codebase. Ruby metrics are explained in detail.
how to rate a Rails application
how to rate a Rails application
ehuard
In some situations, it's useful to be able to evaluate a Rails application quickly. I talk about how I work to get the most data as possible to get a good picture of whether an application is well-maintained, and will be easy to maintain later.
12 Hours To Rate A Rails Application
12 Hours To Rate A Rails Application
ehuard
thought experiment about how to find objects in the home quicky using technology (while tidying up and putting the objects in the right place is obviously the correct solution)
Barcamp Ghent2009
Barcamp Ghent2009
ehuard
realtimeweb, webhooks, juggernaut,hype
The real-time web
The real-time web
ehuard
The internet of thing is hot. This talk describes the trends that led to this phenomenon. Augmented reality links online content to physical object - i talk about the different ways this can happen. Then i talk about physical computing: making things talk, using Arduino, mainly.
Rails and the internet of things
Rails and the internet of things
ehuard
OAuth protocol - keeping your password to yourself in sharing of resources between sites.
Oauth
Oauth
ehuard
Plus de ehuard
(15)
Euroclojure 2017
Euroclojure 2017
Ruby goes to Hollywood
Ruby goes to Hollywood
Ruby hollywood nordic
Ruby hollywood nordic
Ruby goes to hollywood
Ruby goes to hollywood
Ruby hollywood
Ruby hollywood
Concurrency: Rubies, plural
Concurrency: Rubies, plural
Concurrency
Concurrency
Concurrency
Concurrency
12 hours to rate a rails application
12 hours to rate a rails application
how to rate a Rails application
how to rate a Rails application
12 Hours To Rate A Rails Application
12 Hours To Rate A Rails Application
Barcamp Ghent2009
Barcamp Ghent2009
The real-time web
The real-time web
Rails and the internet of things
Rails and the internet of things
Oauth
Oauth
Dernier
Platform Engineering vs SRE discussion and lessons learnt.
Working together SRE & Platform Engineering
Working together SRE & Platform Engineering
Marcus Vechiato
Keynote talk by Mark Billinghurst at the 9th XR-Metaverse conference in Busan, South Korea. The talk was given on May 20th, 2024. It talks about progress on achieving the Metaverse vision laid out in Neil Stephenson's book, Snowcrash.
The Metaverse: Are We There Yet?
The Metaverse: Are We There Yet?
Mark Billinghurst
що таке продакт менеджмент? про професію і карєру продактів для світчерів та початківців.
Intro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджера
Mark Opanasiuk
Keynote at "14th Temporal Web Analytics" Workshop at the ACM WebConf2024, Singapore, 14 May 2024.
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
Stefan Dietze
FIDO Taipei Workshop: Securing the Edge with FDO
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
FIDO Alliance
FIDO Seminar RSAC 2024
Design Guidelines for Passkeys 2024.pptx
Design Guidelines for Passkeys 2024.pptx
FIDO Alliance
At Skynet Technologies, our team of accessibility experts performs automated, semi-automated, and manual audits of websites and web applications as per WCAG 2.2 level AA, ADA, and section 508. Based on evaluations of the accessibility compliance level of the website’s UI, design, source code, navigation, interactive elements, and overall usability, we will provide a digital accessibility evaluation report with in-depth details of potential accessibility barriers and remediation recommendations. Get a manual website WCAG audit (2.0, 2.1, 2.2 level AA) for a small website: 10 pages: $2,500 within 7 business days 30 pages: $7,500 within 14 business days 50 pages: $12,500 within 28 business days For medium websites: 100 pages: $25,000 within 6 weeks For larger websites or audits of all pages, please reach out hello@skynettechnologies.com.
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Skynet Technologies
Discuss the core tradeoffs and considerations involved in order-free and ordered stream processing. Brian Taylor walks through the pros and cons of three different approaches: no data dependency, deferred inter-event data dependency, and streaming inter-event data dependency.
Event-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Challenges in Stream Processing
ScyllaDB
Discover how to avoid common pitfalls when shifting to an event-driven architecture (EDA) in order to boost system recovery and scalability. We cover Kafka Schema Registry, in-broker transformations, event sourcing, and more.
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
ScyllaDB
TEST BANK For, Information Technology Project Management 9th Edition Kathy Schwalbe.pdf TEST BANK For, Information Technology Project Management 9th Edition Kathy Schwalbe.pdf TEST BANK For, Information Technology Project Management 9th Edition Kathy Schwalbe.pdf
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
marcuskenyatta275
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
中 央社
FIDO Seminar RSAC 2024
Introduction to FIDO Authentication and Passkeys.pptx
Introduction to FIDO Authentication and Passkeys.pptx
FIDO Alliance
Ruby has a lot of standard libraries from Ruby 1.8. I promote them democratically with GitHub today via default and bundled gems. So, I'm working to extract them for Ruby 3.4 continuously and future versions. It's long journey for me. After that, some versions may suddenly happen LoadError at require when running bundle exec or bin/rails, for example matrix or net-smtp. We need to learn what's difference default/bundled gems with standard libraries. In this presentation, I will introduce what's the difficult to extract bundled gems from default gems and the details of the functionality that Ruby's require and bundle exec with default/bundled gems. You can learn how handle your issue about standard libraries.
Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024
Hiroshi SHIBATA
Artificial Intelligence is referred to as machine intelligence, and it is rooted in binary codes and mathematical algorithms. It is a testament to human creativity and is capable of massive data processing, pattern recognition, and even self-learning. However, the realm of AI realm is confined.
AI mind or machine power point presentation
AI mind or machine power point presentation
yogeshlabana357357
Slides for my "WebRTC-to-SIP and back: it's not all about audio and video" presentation at the OpenSIPS Summit 2024. They describe my prototype efforts to add gatewaying support for a few SIP application protocols (T.140 for real-time text and MSRP) to Janus via data channels, with the related implementation challenges and the interesting opportunities they open.
WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024
Lorenzo Miniero
Are you wondering why everyone is talking about the Flutterwave scandal? You’re not alone! It’s been in the news a lot. We’re going to tell you all about the Flutterwave Scandal in a way that’s easy to get. Keep reading, because we’re going to share the whole story with you. The company Flutterwave is headquartered in San Francisco, California, United States. In 2016, Iyinoluwa Aboyeji, Olugbenga Agboola, and Adeleke Adekoya established Flutterwave. It offers a payment infrastructure to international merchants and payment service providers throughout Africa. The company operates in various African countries including Nigeria, Kenya, Uganda, Ghana, South Africa, and others. They focus on digital payments, helping businesses accept and process payments on various channels like the web, mobile, ATM, and POS. Recently, they’ve been in the news due to allegations of misconduct within the company, which has affected their reputation and value. Flutterwave is an essential player in the African fintech landscape, aiming to drive growth for banks and businesses through digital payment solutions. The Flutterwave scandal involves allegations of misconduct and inappropriate behaviour towards female employees by the company’s co-founder and CEO, Olugbenga Agboola. Reports have surfaced from both current and former employees about bullying, intimidation, and sexual harassment at work. The allegations of inappropriate behaviour towards female employees at Flutterwave, specifically involving the CEO Olugbenga Agboola, were brought to public attention in April 2022.This was when Clara Wanjiku Odero, an ex-employee and current CEO of Credrails, published a Medium post and a series of tweets on April 4, 2022, accusing Flutterwave and Agboola of bullying. These allegations were part of a broader range of misconduct claims that surfaced around the same time The reasons behind the scandal are rooted in accusations of unethical behavior within the company. The allegations suggest a workplace culture that allowed for misconduct and failed to protect employees from harassment and intimidation. Specifically, the Flutterwave scandal refers to the series of events where the CEO was accused of engaging in improper conduct with female colleagues. This led to a broader investigation into the company’s practices and raised serious concerns about the fintech’s corporate governance. The scandal had significant repercussions, including a drop in the company’s stock price and a loss of trust among customers and partners. The trust that customers and investors had in Flutterwave was greatly damaged. People started to doubt the company’s integrity and whether their money and personal information were safe. Market Impact The scandal shook the entire fintech market. Flutterwave’s competitors saw this as an opportunity and started to attract customers who were leaving Flutterwave.
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
UK Journal
In today’s fast-paced digital world, harnessing the power of artificial intelligence (AI) can significantly enhance productivity and creativity across various domains. With the advent of advanced language models like ChatGPT, developers, marketers, data analysts, and professionals in numerous other fields can now leverage AI-generated prompts to spark innovative ideas and streamline their workflows.
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
iSEO AI
FIDO Taipei Workshop: Securing the Edge with FDO
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FIDO Alliance
FIDO Seminar RSAC 2024
Intro to Passkeys and the State of Passwordless.pptx
Intro to Passkeys and the State of Passwordless.pptx
FIDO Alliance
Webinar Recording: https://www.panagenda.com/webinars/easier-faster-and-more-powerful-notes-document-properties-reimagined/ Have you ever felt frustrated by the small properties dialog in Notes? Had to create an agent or button to quickly change a field? Searched endlessly for the field you wanted to compare each time you selected a new document? Wished you could just make the damned thing bigger? Luckily, there is a solution – and you probably already have it installed! With the free panagenda Document Properties (Pro) you get the properties dialog you always needed. Big, resizable, full-text searchable. View multiple documents at once or compare them with a diff viewer. Modify any field, and finally have an easy way to handle profile documents for all users. Join HCL Lifetime Ambassador Julian Robichaux to discover how Document Properties can simplify your work and assist you daily when using Domino applications – in the client or the designer. You will never look back! Key takeaways from this session - What Document Properties is, which editions there are, and how you can find it in Notes and Domino Designer - How you can search for and edit any field, compare documents, or CSV export all data - How to find, edit, and even delete profile documents - Which configuration settings are available to customize feature
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
panagenda
Dernier
(20)
Working together SRE & Platform Engineering
Working together SRE & Platform Engineering
The Metaverse: Are We There Yet?
The Metaverse: Are We There Yet?
Intro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджера
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
Collecting & Temporal Analysis of Behavioral Web Data - Tales From The Inside
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Introduction to FDO and How It works Applications _ Richard at FIDO Alliance.pdf
Design Guidelines for Passkeys 2024.pptx
Design Guidelines for Passkeys 2024.pptx
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Event-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Challenges in Stream Processing
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
Event-Driven Architecture Masterclass: Engineering a Robust, High-performance...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
Introduction to FIDO Authentication and Passkeys.pptx
Introduction to FIDO Authentication and Passkeys.pptx
Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024
AI mind or machine power point presentation
AI mind or machine power point presentation
WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
FDO for Camera, Sensor and Networking Device – Commercial Solutions from VinC...
Intro to Passkeys and the State of Passwordless.pptx
Intro to Passkeys and the State of Passwordless.pptx
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
Tokyo Cabinet
1.
Tokyo Cabinet Elise
Huard – BRUG meeting 27/08/2009
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3.
http://www.slideshare.net/estraier/introduction-to-tokyo-products?src=embed
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FAST 0.7s to
store 10 6 in hash table 1.6s to store 10 6 in Btree table
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http://www.igvita.com/2009/07/13/extending-tokyo-cabinet-db-with-lua/
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