This document discusses Cassandra time series data challenges and Threat Stack's solutions. Typical problems include disks filling quickly and data losing value over time. Threat Stack handles 5-10TB of data daily with 80,000-150,000 transactions per second. They developed their own MTCS compaction strategy and sstablejanitor tool to better handle time series data expiration in Cassandra by unlinking expired SSTables. This allows them to analyze large volumes of real-time security event data cost effectively at scale.
The Cassandra architecture shines at ensuring a very high availability of data even while nodes are failing or are overloaded. On the other hand, query latency will often rise during these events, especially on the higher percentiles. Many improvements have been made to reduce this effect over the past years. This talk will focus on one in particular: Speculative Retries. Introduced in Cassandra 2.0 on the server side and in the Java Driver 3.0 on the client side, this strategy remains complex to fully understand and to finely tune. This talk will deep dive into theoretical and practical aspects of Speculative Retries, showing the effect of tuning strategies with ad-hoc benchmarks.
About the Speakers
Michael Figuiere Cloud Platform Engineer, Netflix
Michael is a senior software engineer at Netflix where he works on improving the cloud storage infrastructure. He previously worked at Apple and DataStax where he worked for several years on creating Drivers and Developer Tools for Cassandra. At ease with both enterprise applications and lower level technologies, he specializes in distributed architectures and topics such as databases, search engines, and cloud.
Minh Do Senior Distributed Engineer, Netflix
Minh Do has been working at Netflix for the last several years to run, patch, and troubleshoot Cassandra on both server and client sides, and is also a co-creator of Dynomite project. Prior to Netflix, at Tango, he spearheaded its Big Data pipeline system from the ground using Spark/Hadoop. Before that, at Qualys, he built a distributed queue system that bridges traffics between all major components. He has passion in distributed system, machine learning/deep learning, and data storages.
Discussion about the evolution of metrics in Cassandra from 1.0 to 3.0, how the metric changes impact operational tooling, pros and cons for different metric representations, and how and why DataStax OpsCenter collects and stores metrics. Includes a deep dive on how DataStax OpsCenter represents and stores the different kinds of metrics to provide visibility beyond simple cluster averages both behind the scenes and in the rendering.
About the Speaker
Chris Lohfink Software Engineer, DataStax
I am a Java, Python, and Clojure developer who has been using Cassandra in an application development and operational context for the last five years. The last nearly two years I have been working with the OpsCenter Monitoring team at DataStax to improve the accuracy and breadth of the visualization tooling available.
Cassandra is the dominant data store used at Netflix and it's health is critical to many of its services. In this talk we will share details of the recent redesign of our health monitoring system and how we leveraged a reactive stream processing system to give us a real-time view our entire fleet while dramatically improving accuracy and reducing false alarms in our alerting.
About the Speaker
Jason Cacciatore Senior Software Engineer, Netflix
Jason Cacciatore is a Senior Software Engineer at Netflix, where he's been working for the past several years. He's interested in stateful distributed systems and has a diverse background in technology. In his spare time he enjoys spending time with his wife and two sons, reading non-fiction, and watching Netflix documentaries.
What We Learned About Cassandra While Building go90 (Christopher Webster & Th...DataStax
Go90 is a mobile entertainment platform offering access to live and on demand videos. We built the web services platform and social features like activity feed for go90 by making heavy use of Cassandra and Scala, and would like to share what we learned during development and while operating go90. In this presentation, we cover our data model evolution from the initial prototypes to the current production version and the significant performance gain by using a better data model. We will explain how we apply time series data modeling and the benefits of using expiring columns with DateTieredCompactionStrategy. We will also talk about interesting experiences related to table modifications, tombstones and table pagination. On the operations side, we will discuss our findings on java driver usage, performance, monitoring, cluster maintenance, version upgrade, 2-way ssl and many more. We hope you can learn from our mistakes instead of making them yourself!
About the Speakers
Christopher Webster Software Engineer, AOL
Christopher Webster works on the web services platform for the go90 AOL project. Previously he was a Computer Scientist for the Mission Control Technologies project at NASA Ames Center. Chris worked as a senior staff engineer at Sun Microsystems for Project zembly, the cloud development and deployment environment as well as technical lead in many NetBeans projects. Chris is an author of the NetBeans Field Guide and Assemble the Social Web With Zembly.
Thomas Ng Software Engineer, AOL
Thomas Ng is a software engineer at AOL, building web services for the go90 mobile entertainment platform using Cassandra, Scala and Kafka.
One Billion Black Friday Shoppers on a Distributed Data Store (Fahd Siddiqui,...DataStax
EmoDB is an open source RESTful data store built on top of Cassandra that stores JSON documents and, most notably, offers a databus that allows subscribers to watch for changes to those documents in real time. It features massive non-blocking global writes, asynchronous cross data center communication, and schema-less json content.
For non-blocking global writes, we created a ""JSON delta"" specification that defines incremental updates to any json document. Each row, in Cassandra, is thus a sequence of deltas that serves as a Conflict-free Replicated Datatype (CRDT) for EmoDB's system of record. We introduce the concept of ""distributed compactions"" to frequently compact these deltas for efficient reads.
Finally, the databus forms a crucial piece of our data infrastructure and offers a change queue to real time streaming applications.
About the Speaker
Fahd Siddiqui Lead Software Engineer, Bazaarvoice
Fahd Siddiqui is a Lead Software Engineer at Bazaarvoice in the data infrastructure team. His interests include highly scalable, and distributed data systems. He holds a Master's degree in Computer Engineering from the University of Texas at Austin, and frequently talks at Austin C* User Group. About Bazaarvoice: Bazaarvoice is a network that connects brands and retailers to the authentic voices of people where they shop. More at www.bazaarvoice.com
Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...DataStax
Cassandra databases at Spotify hold all sorts of interesting data sets. Quite obviously, we would like to allow our data scientists tap these data sets.
Recent developments in the offerings of cloud vendors allowed us to engineer systems that answer this use case in an unprecedented way.
In this talk we'll present how we turned the process of exporting data from Cassandra clusters into a trivially parallelizible problem. Using just a few basic cloud products we've managed to dump our largest clusters containing terabytes of data in the order of minutes.
About the Speaker
Emilio Del Tessandoro Software Engineer, Spotify
Emilio Del Tessandoro is a software engineer working on tooling and automation for the Spotify storage infrastructure. He is interested in theoretical computer science with a focus on algorithms and scalable systems.
This presentation will investigate how using micro-batching for submitting writes to Cassandra can improve throughput and reduce client application CPU load.
Micro-batching combines writes for the same partition key into a single network request and ensures they hit the "fast path" for writes on a Cassandra node.
About the Speaker
Adam Zegelin Technical Co-founder, Instaclustr
As Instaclustrs founding software engineer, Adam provides the foundation knowledge of our capability and engineering environment. He delivers business-focused value to our code-base and overall capability architecture. Adam is also focused on providing Instaclustr's contribution to the broader open source community on which our products and services rely, including Apache Cassandra, Apache Spark and other technologies such as CoreOS and Docker.
The Cassandra architecture shines at ensuring a very high availability of data even while nodes are failing or are overloaded. On the other hand, query latency will often rise during these events, especially on the higher percentiles. Many improvements have been made to reduce this effect over the past years. This talk will focus on one in particular: Speculative Retries. Introduced in Cassandra 2.0 on the server side and in the Java Driver 3.0 on the client side, this strategy remains complex to fully understand and to finely tune. This talk will deep dive into theoretical and practical aspects of Speculative Retries, showing the effect of tuning strategies with ad-hoc benchmarks.
About the Speakers
Michael Figuiere Cloud Platform Engineer, Netflix
Michael is a senior software engineer at Netflix where he works on improving the cloud storage infrastructure. He previously worked at Apple and DataStax where he worked for several years on creating Drivers and Developer Tools for Cassandra. At ease with both enterprise applications and lower level technologies, he specializes in distributed architectures and topics such as databases, search engines, and cloud.
Minh Do Senior Distributed Engineer, Netflix
Minh Do has been working at Netflix for the last several years to run, patch, and troubleshoot Cassandra on both server and client sides, and is also a co-creator of Dynomite project. Prior to Netflix, at Tango, he spearheaded its Big Data pipeline system from the ground using Spark/Hadoop. Before that, at Qualys, he built a distributed queue system that bridges traffics between all major components. He has passion in distributed system, machine learning/deep learning, and data storages.
Discussion about the evolution of metrics in Cassandra from 1.0 to 3.0, how the metric changes impact operational tooling, pros and cons for different metric representations, and how and why DataStax OpsCenter collects and stores metrics. Includes a deep dive on how DataStax OpsCenter represents and stores the different kinds of metrics to provide visibility beyond simple cluster averages both behind the scenes and in the rendering.
About the Speaker
Chris Lohfink Software Engineer, DataStax
I am a Java, Python, and Clojure developer who has been using Cassandra in an application development and operational context for the last five years. The last nearly two years I have been working with the OpsCenter Monitoring team at DataStax to improve the accuracy and breadth of the visualization tooling available.
Cassandra is the dominant data store used at Netflix and it's health is critical to many of its services. In this talk we will share details of the recent redesign of our health monitoring system and how we leveraged a reactive stream processing system to give us a real-time view our entire fleet while dramatically improving accuracy and reducing false alarms in our alerting.
About the Speaker
Jason Cacciatore Senior Software Engineer, Netflix
Jason Cacciatore is a Senior Software Engineer at Netflix, where he's been working for the past several years. He's interested in stateful distributed systems and has a diverse background in technology. In his spare time he enjoys spending time with his wife and two sons, reading non-fiction, and watching Netflix documentaries.
What We Learned About Cassandra While Building go90 (Christopher Webster & Th...DataStax
Go90 is a mobile entertainment platform offering access to live and on demand videos. We built the web services platform and social features like activity feed for go90 by making heavy use of Cassandra and Scala, and would like to share what we learned during development and while operating go90. In this presentation, we cover our data model evolution from the initial prototypes to the current production version and the significant performance gain by using a better data model. We will explain how we apply time series data modeling and the benefits of using expiring columns with DateTieredCompactionStrategy. We will also talk about interesting experiences related to table modifications, tombstones and table pagination. On the operations side, we will discuss our findings on java driver usage, performance, monitoring, cluster maintenance, version upgrade, 2-way ssl and many more. We hope you can learn from our mistakes instead of making them yourself!
About the Speakers
Christopher Webster Software Engineer, AOL
Christopher Webster works on the web services platform for the go90 AOL project. Previously he was a Computer Scientist for the Mission Control Technologies project at NASA Ames Center. Chris worked as a senior staff engineer at Sun Microsystems for Project zembly, the cloud development and deployment environment as well as technical lead in many NetBeans projects. Chris is an author of the NetBeans Field Guide and Assemble the Social Web With Zembly.
Thomas Ng Software Engineer, AOL
Thomas Ng is a software engineer at AOL, building web services for the go90 mobile entertainment platform using Cassandra, Scala and Kafka.
One Billion Black Friday Shoppers on a Distributed Data Store (Fahd Siddiqui,...DataStax
EmoDB is an open source RESTful data store built on top of Cassandra that stores JSON documents and, most notably, offers a databus that allows subscribers to watch for changes to those documents in real time. It features massive non-blocking global writes, asynchronous cross data center communication, and schema-less json content.
For non-blocking global writes, we created a ""JSON delta"" specification that defines incremental updates to any json document. Each row, in Cassandra, is thus a sequence of deltas that serves as a Conflict-free Replicated Datatype (CRDT) for EmoDB's system of record. We introduce the concept of ""distributed compactions"" to frequently compact these deltas for efficient reads.
Finally, the databus forms a crucial piece of our data infrastructure and offers a change queue to real time streaming applications.
About the Speaker
Fahd Siddiqui Lead Software Engineer, Bazaarvoice
Fahd Siddiqui is a Lead Software Engineer at Bazaarvoice in the data infrastructure team. His interests include highly scalable, and distributed data systems. He holds a Master's degree in Computer Engineering from the University of Texas at Austin, and frequently talks at Austin C* User Group. About Bazaarvoice: Bazaarvoice is a network that connects brands and retailers to the authentic voices of people where they shop. More at www.bazaarvoice.com
Cassandra Exports as a Trivially Parallelizable Problem (Emilio Del Tessandor...DataStax
Cassandra databases at Spotify hold all sorts of interesting data sets. Quite obviously, we would like to allow our data scientists tap these data sets.
Recent developments in the offerings of cloud vendors allowed us to engineer systems that answer this use case in an unprecedented way.
In this talk we'll present how we turned the process of exporting data from Cassandra clusters into a trivially parallelizible problem. Using just a few basic cloud products we've managed to dump our largest clusters containing terabytes of data in the order of minutes.
About the Speaker
Emilio Del Tessandoro Software Engineer, Spotify
Emilio Del Tessandoro is a software engineer working on tooling and automation for the Spotify storage infrastructure. He is interested in theoretical computer science with a focus on algorithms and scalable systems.
This presentation will investigate how using micro-batching for submitting writes to Cassandra can improve throughput and reduce client application CPU load.
Micro-batching combines writes for the same partition key into a single network request and ensures they hit the "fast path" for writes on a Cassandra node.
About the Speaker
Adam Zegelin Technical Co-founder, Instaclustr
As Instaclustrs founding software engineer, Adam provides the foundation knowledge of our capability and engineering environment. He delivers business-focused value to our code-base and overall capability architecture. Adam is also focused on providing Instaclustr's contribution to the broader open source community on which our products and services rely, including Apache Cassandra, Apache Spark and other technologies such as CoreOS and Docker.
Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...DataStax
Customizing JVM settings for the needs of an application can be a tricky business, especially when running externally developed software such as Cassandra. In this talk I will share our experiences and the procedure that we have used to test and validate changes with Java tuning. We'll explore with two recent experiences: changes and monitoring of G1 garbage collection, and moving buffer objects off the heap.
For the talk, I'll discuss our tuning process at Knewton. I will share some of the challenges that we faced while identifying what we expected to learn. I'll discuss how we isolated and minimized variables across tests, the importance of the duration of these tests, and how we try to separate correlation from causation. I will demonstrate how to use and interpret the results of the custom scripts that we were driven to develop to gain visibility into our G1GC processes; these scripts will be open sourced.
About the Speaker
Carlos Monroy Senior Software Engineer, Knewton
Carlos Monroy is a senior engineer on the database team at Knewton, an education company that created an adaptive learning platform. Carlos has been developing software professionally since 1998. His experience holding multiple roles on the software lifecycle provides him a wholistic approach. Having used over a half dozen relational database engines, he has recently come over to the NoSQL side, first working with HBase and for the last three years Cassandra.
Clock Skew and Other Annoying Realities in Distributed Systems (Donny Nadolny...DataStax
You write with QUORUM, you read with QUORUM. You're safe, right?
Although it may seem that way, you could read a different value than the one you wrote - even if nobody else wrote after you. One way this can happen is if the time on the machines in your cluster is not synchronized closely enough. This is called clock skew, and is just one of the ways you'll see that this anomaly can occur.
In this talk we'll dive in to how Cassandra handles conflicting data, walk through several weird and seemingly impossible situations that can happen (both with and without clock skew), and see what we can do to work around them.
About the Speaker
Donny Nadolny Senior Developer, PagerDuty
Donny Nadolny is a Scala developer at PagerDuty, working on improving the reliability of their backend systems. He spends a large amount of time investigating problems experienced with distributed systems like Cassandra and ZooKeeper.
Beginning Operations: 7 Deadly Sins for Apache Cassandra OpsDataStax Academy
The internal battle has been fought, and Cassandra is your group's NoSQL platform of choice! Hooray! But now what? This talk will introduce you to all the basic operations concepts you need to know to start your foray into the wonderful world of Cassandra off right. Or even if you have already started but are looking for a solid holistic overview... this is the talk for you!
PlayStation and Cassandra Streams (Alexander Filipchik & Dustin Pham, Sony) |...DataStax
After reading the topic you are probably asking yourself: “Why I’ve never heard about Cassandra Streams?”. The reason is because Cassandra didn’t have any streams support. Until now.
The project started as a preparation to multi regional deployment, so we needed to test Cassandra and answer several simple questions:
· what will be the replication lag, or how long will it take for each mutation to propagate?
· will we be losing any mutation?
· will we see any additional load and/or other problems?
· and zillions of other questions
To answer them, we decided to integrate Cassandra with Amazon Kinesis, so we can track any individual mutation and analyze replication stats. That is how our Cassandra Streams integration was born. Currently it supports several stream platforms, like Kinesis and Kafka.
During this talk you will learn how we did it, how we used it to test Cassandra in Multi-regional setup and what are other possible applications of this concept.
About the Speaker
Dustin Pham, Sony
Dustin is part of the small team who built the core infrastructure which delivered the PlayStation 3 store and then subsequently core services for the PlayStation 4. He has been with Sony for over 4 years and continues to focus on providing entertainment experiences to Sony customers. Dustin is an avid gamer and finds enjoyment in solving large scale problems.
Co-Founder and CTO of Instaclustr, Ben Bromhead's presentation at the Cassandra Summit 2016, in San Jose.
This presentation will show how create truly elastic Cassandra deployments on AWS allowing you to scale and shrink your large Cassandra deployments multiple times a day. Leveraging a combination of EBS backed disks, JBOD, token pinning and our previous work on bootstrapping from backups you will be able to dramatically reduce costs per cluster by scaling to match your daily workloads.
Cassandra gives operations a lot of control over the system by forcing them to make a lot of decisions they'd rather not around cluster topology changes. Hecuba2 is a tool that helps to automate that. Hecuba2 has a library component and an agent component. The library provides an API for manipulating Cassandra topologies and the agent runs on all Cassandra hosts and converges the existing topology to the generated topology.
Hecuba2 is running in production at Spotify and has been remarkably bug free since being rolled out. It supports creating a cluster, expanding a cluster, and replacing nodes.
This talk will cover the design of Hecuba2 and how to deploy it.
About the Speaker
Radovan Zvoncek Backend Engineer, Spotify
After graduating a master degree in distributed systems I've joined Spotify as a backend engineer. For the past three years I've been involved in Cassandra operations, as well as the cultivation of the Cassandra ecosystem at Spotify.
Building a Multi-Region Cluster at Target (Aaron Ploetz, Target) | Cassandra ...DataStax
Lessons learned from a year spent building a Cassandra cluster over multiple regions, data centers, and providers. Will discuss our successes and learnings on replication, operations, and application development.
About the Speaker
Aaron Ploetz Lead Technical Architect, Target
Aaron is a Lead Technical Architect for Target, where he coaches development teams on modeling and building applications for Cassandra. He is active in the Cassandra tags on StackOverflow, and has also contributed patches to cqlsh. Aaron holds a B.S. in Management/Computer Systems from the University of Wisconsin-Whitewater, a M.S. in Software Engineering and Database Technologies from Regis University, and is a 2x DataStax MVP for Apache Cassandra.
Optimizing Your Cluster with Coordinator Nodes (Eric Lubow, SimpleReach) | Ca...DataStax
With the addition of vnodes (Virtual Nodes), Cassandra users were able to gain a few benefits as a result of streaming when it came to bootstrapping and decommissioning nodes. On the flip side, having to route requests on larger clusters became a lot more intensive of a workload for all nodes that were then forced to act coordinator nodes. By setting up a tier of proxy nodes, we were able to have our cluster of 50 nodes perform with a 300% improvement on average in a mixed workload environment. This is an explanation of what we did, how we did it, and why it works.
About the Speaker
Eric Lubow CTO, SimpleReach
Eric Lubow is CTO of SimpleReach, where he builds highly-scalable distributed systems for processing analytics data. Eric is also a DataStax MVP for Cassandra, and co-author of Practical Cassandra. In his spare time, Eric is a skydiver, motorcycle rider, mixed martial artist, and dog dad.
A Detailed Look At cassandra.yaml (Edward Capriolo, The Last Pickle) | Cassan...DataStax
Successfully running Apache Cassandra in production often means knowing what configuration settings to change and which ones to leave as default. Over the years the cassandra.yaml file has grown to provide a number of settings that can improve stability and performance. While the file contains plenty of helpful comments, there is more to be said about the settings and when to change them.
In this talk Edward Capriolo, Consultant at The Last Pickle, will break down the parameters in the configuration files. Looking at those that are essential to getting started, those that impact performance, those that improve availability, the exotic ones, and the ones that should not be played with. This talk is ideal for someone someone setting up Cassandra for the first time up to people with deployments in productions and wondering what the more exotic configuration options do.
About the Speaker
Edward Capriolo Consultant, The Last Pickle
Long time Apache Cassandra user, big data enthusiast.
We have been offering many internet services and smart phone applications for over 20 years in Japan, and Cassandra has been used by our services since 2010. In this presentation, I will explain some issues and solutions about Cassandra, and our next generation infrastructure for Cassandra.
About the Speaker
Satoshi Konno Technical Manager, Yahoo Japan Corporation
Satoshi Konno is a software engineer with 20 years of experience. He has worked in Yahoo Japan as a programmer for 10 years and in their NoSQL team for the past 4 years and he is currently in a computer science doctoral course studying distributed computing.
Webinar: Getting Started with Apache CassandraDataStax
Would you like to learn how to use Cassandra but don’t know where to begin? Want to get your feet wet but you’re lost in the desert? Longing for a cluster when you don’t even know how to set up a node? Then look no further! Rebecca Mills, Junior Evangelist at Datastax, will guide you in the webinar “Getting Started with Apache Cassandra...”
You'll get an overview of Planet Cassandra’s resources to get you started quickly and easily. Rebecca will take you down the path that's right for you, whether you are a developer or administrator. Join if you are interested in getting Cassandra up and working in the way that suits you best.
Building a Distributed Reservation System with Cassandra (Andrew Baker & Jeff...DataStax
At Choice Hotels International, we are in the midst of a multi-year effort to replace our 25 year old monolithic reservation system with a cloud-based, microservice-style architecture using Cassandra. Since processing the first live reservation on the new system in December 2015, we've been shifting an increasing amount of shopping and booking traffic to the new system, with retirement of the old system scheduled for early 2017.
After a quick review of our problem space, architecture, schema design, and Cassandra deployment, we'll take a closer look several challenges we faced and discuss how they impacted our data modeling, development and deployment:
* Managing data with varying consistency requirements
* Maintaining data integrity across microservice boundaries
* Performing complex queries involving overlapping time ranges
* Relying on time-to-live (TTL) for data cleanup
* Balancing denormalization, performance and cost
About the Speakers
Andrew Baker Senior Software Engineer, Choice Hotels International
Andrew is the technical lead of the service development team responsible for storage and maintenance of rates and reservations for thousands of hotels around the world.
Jeffrey Carpenter Systems Architect, Choice Hotels International
Jeff Carpenter is a software and systems architect with experience in the hospitality and defense industries, it. Jeff is currently working on a cloud-based hotel reservation system using Cassandra and is the author of the new O'Reilly book "Cassandra: The Definitive Guide, 2nd edition".
The Promise and Perils of Encrypting Cassandra Data (Ameesh Divatia, Baffle, ...DataStax
Why do data breaches occur even though we protect data at rest and in flight? What if the Cassandra admin's credentials get compromised? Why is it so hard to make encryption work for real world applications? If I encrypt my customer's data, do I have to turn it over when the authorities come calling? The answer may be in keeping data encrypted. . .always, let the customer own the keys and make data breaches irrelevant.
In this talk, Ameesh Divatia, Co-founder at Baffle.io, will talk about a way to encrypt individual fields in a Cassandra database while continuing to let them be available for CQL access. From deterministic to random algorithms, key management and integration into DataStax drivers, this talk will introduce attendees to the steps to follow in order to protect an existing Cassandra database with field-level granularity ensuring protection against data breaches.
About the Speaker
Ameesh Divatia President & CEO, Baffle, Inc.
Ameesh is a serial entrepreneur with over 25 years of operating experience in storage, security and networking infrastructure. He specializes in conceiving and implementing startup business plans that create new product categories by leveraging innovation in existing markets to its adjacencies. He co-founded Baffle in May 2015 to address the challenge of preventing data breaches in cloud infrastructure.
Lessons Learned on Java Tuning for Our Cassandra Clusters (Carlos Monroy, Kne...DataStax
Customizing JVM settings for the needs of an application can be a tricky business, especially when running externally developed software such as Cassandra. In this talk I will share our experiences and the procedure that we have used to test and validate changes with Java tuning. We'll explore with two recent experiences: changes and monitoring of G1 garbage collection, and moving buffer objects off the heap.
For the talk, I'll discuss our tuning process at Knewton. I will share some of the challenges that we faced while identifying what we expected to learn. I'll discuss how we isolated and minimized variables across tests, the importance of the duration of these tests, and how we try to separate correlation from causation. I will demonstrate how to use and interpret the results of the custom scripts that we were driven to develop to gain visibility into our G1GC processes; these scripts will be open sourced.
About the Speaker
Carlos Monroy Senior Software Engineer, Knewton
Carlos Monroy is a senior engineer on the database team at Knewton, an education company that created an adaptive learning platform. Carlos has been developing software professionally since 1998. His experience holding multiple roles on the software lifecycle provides him a wholistic approach. Having used over a half dozen relational database engines, he has recently come over to the NoSQL side, first working with HBase and for the last three years Cassandra.
Clock Skew and Other Annoying Realities in Distributed Systems (Donny Nadolny...DataStax
You write with QUORUM, you read with QUORUM. You're safe, right?
Although it may seem that way, you could read a different value than the one you wrote - even if nobody else wrote after you. One way this can happen is if the time on the machines in your cluster is not synchronized closely enough. This is called clock skew, and is just one of the ways you'll see that this anomaly can occur.
In this talk we'll dive in to how Cassandra handles conflicting data, walk through several weird and seemingly impossible situations that can happen (both with and without clock skew), and see what we can do to work around them.
About the Speaker
Donny Nadolny Senior Developer, PagerDuty
Donny Nadolny is a Scala developer at PagerDuty, working on improving the reliability of their backend systems. He spends a large amount of time investigating problems experienced with distributed systems like Cassandra and ZooKeeper.
Beginning Operations: 7 Deadly Sins for Apache Cassandra OpsDataStax Academy
The internal battle has been fought, and Cassandra is your group's NoSQL platform of choice! Hooray! But now what? This talk will introduce you to all the basic operations concepts you need to know to start your foray into the wonderful world of Cassandra off right. Or even if you have already started but are looking for a solid holistic overview... this is the talk for you!
PlayStation and Cassandra Streams (Alexander Filipchik & Dustin Pham, Sony) |...DataStax
After reading the topic you are probably asking yourself: “Why I’ve never heard about Cassandra Streams?”. The reason is because Cassandra didn’t have any streams support. Until now.
The project started as a preparation to multi regional deployment, so we needed to test Cassandra and answer several simple questions:
· what will be the replication lag, or how long will it take for each mutation to propagate?
· will we be losing any mutation?
· will we see any additional load and/or other problems?
· and zillions of other questions
To answer them, we decided to integrate Cassandra with Amazon Kinesis, so we can track any individual mutation and analyze replication stats. That is how our Cassandra Streams integration was born. Currently it supports several stream platforms, like Kinesis and Kafka.
During this talk you will learn how we did it, how we used it to test Cassandra in Multi-regional setup and what are other possible applications of this concept.
About the Speaker
Dustin Pham, Sony
Dustin is part of the small team who built the core infrastructure which delivered the PlayStation 3 store and then subsequently core services for the PlayStation 4. He has been with Sony for over 4 years and continues to focus on providing entertainment experiences to Sony customers. Dustin is an avid gamer and finds enjoyment in solving large scale problems.
Co-Founder and CTO of Instaclustr, Ben Bromhead's presentation at the Cassandra Summit 2016, in San Jose.
This presentation will show how create truly elastic Cassandra deployments on AWS allowing you to scale and shrink your large Cassandra deployments multiple times a day. Leveraging a combination of EBS backed disks, JBOD, token pinning and our previous work on bootstrapping from backups you will be able to dramatically reduce costs per cluster by scaling to match your daily workloads.
Cassandra gives operations a lot of control over the system by forcing them to make a lot of decisions they'd rather not around cluster topology changes. Hecuba2 is a tool that helps to automate that. Hecuba2 has a library component and an agent component. The library provides an API for manipulating Cassandra topologies and the agent runs on all Cassandra hosts and converges the existing topology to the generated topology.
Hecuba2 is running in production at Spotify and has been remarkably bug free since being rolled out. It supports creating a cluster, expanding a cluster, and replacing nodes.
This talk will cover the design of Hecuba2 and how to deploy it.
About the Speaker
Radovan Zvoncek Backend Engineer, Spotify
After graduating a master degree in distributed systems I've joined Spotify as a backend engineer. For the past three years I've been involved in Cassandra operations, as well as the cultivation of the Cassandra ecosystem at Spotify.
Building a Multi-Region Cluster at Target (Aaron Ploetz, Target) | Cassandra ...DataStax
Lessons learned from a year spent building a Cassandra cluster over multiple regions, data centers, and providers. Will discuss our successes and learnings on replication, operations, and application development.
About the Speaker
Aaron Ploetz Lead Technical Architect, Target
Aaron is a Lead Technical Architect for Target, where he coaches development teams on modeling and building applications for Cassandra. He is active in the Cassandra tags on StackOverflow, and has also contributed patches to cqlsh. Aaron holds a B.S. in Management/Computer Systems from the University of Wisconsin-Whitewater, a M.S. in Software Engineering and Database Technologies from Regis University, and is a 2x DataStax MVP for Apache Cassandra.
Optimizing Your Cluster with Coordinator Nodes (Eric Lubow, SimpleReach) | Ca...DataStax
With the addition of vnodes (Virtual Nodes), Cassandra users were able to gain a few benefits as a result of streaming when it came to bootstrapping and decommissioning nodes. On the flip side, having to route requests on larger clusters became a lot more intensive of a workload for all nodes that were then forced to act coordinator nodes. By setting up a tier of proxy nodes, we were able to have our cluster of 50 nodes perform with a 300% improvement on average in a mixed workload environment. This is an explanation of what we did, how we did it, and why it works.
About the Speaker
Eric Lubow CTO, SimpleReach
Eric Lubow is CTO of SimpleReach, where he builds highly-scalable distributed systems for processing analytics data. Eric is also a DataStax MVP for Cassandra, and co-author of Practical Cassandra. In his spare time, Eric is a skydiver, motorcycle rider, mixed martial artist, and dog dad.
A Detailed Look At cassandra.yaml (Edward Capriolo, The Last Pickle) | Cassan...DataStax
Successfully running Apache Cassandra in production often means knowing what configuration settings to change and which ones to leave as default. Over the years the cassandra.yaml file has grown to provide a number of settings that can improve stability and performance. While the file contains plenty of helpful comments, there is more to be said about the settings and when to change them.
In this talk Edward Capriolo, Consultant at The Last Pickle, will break down the parameters in the configuration files. Looking at those that are essential to getting started, those that impact performance, those that improve availability, the exotic ones, and the ones that should not be played with. This talk is ideal for someone someone setting up Cassandra for the first time up to people with deployments in productions and wondering what the more exotic configuration options do.
About the Speaker
Edward Capriolo Consultant, The Last Pickle
Long time Apache Cassandra user, big data enthusiast.
We have been offering many internet services and smart phone applications for over 20 years in Japan, and Cassandra has been used by our services since 2010. In this presentation, I will explain some issues and solutions about Cassandra, and our next generation infrastructure for Cassandra.
About the Speaker
Satoshi Konno Technical Manager, Yahoo Japan Corporation
Satoshi Konno is a software engineer with 20 years of experience. He has worked in Yahoo Japan as a programmer for 10 years and in their NoSQL team for the past 4 years and he is currently in a computer science doctoral course studying distributed computing.
Webinar: Getting Started with Apache CassandraDataStax
Would you like to learn how to use Cassandra but don’t know where to begin? Want to get your feet wet but you’re lost in the desert? Longing for a cluster when you don’t even know how to set up a node? Then look no further! Rebecca Mills, Junior Evangelist at Datastax, will guide you in the webinar “Getting Started with Apache Cassandra...”
You'll get an overview of Planet Cassandra’s resources to get you started quickly and easily. Rebecca will take you down the path that's right for you, whether you are a developer or administrator. Join if you are interested in getting Cassandra up and working in the way that suits you best.
Building a Distributed Reservation System with Cassandra (Andrew Baker & Jeff...DataStax
At Choice Hotels International, we are in the midst of a multi-year effort to replace our 25 year old monolithic reservation system with a cloud-based, microservice-style architecture using Cassandra. Since processing the first live reservation on the new system in December 2015, we've been shifting an increasing amount of shopping and booking traffic to the new system, with retirement of the old system scheduled for early 2017.
After a quick review of our problem space, architecture, schema design, and Cassandra deployment, we'll take a closer look several challenges we faced and discuss how they impacted our data modeling, development and deployment:
* Managing data with varying consistency requirements
* Maintaining data integrity across microservice boundaries
* Performing complex queries involving overlapping time ranges
* Relying on time-to-live (TTL) for data cleanup
* Balancing denormalization, performance and cost
About the Speakers
Andrew Baker Senior Software Engineer, Choice Hotels International
Andrew is the technical lead of the service development team responsible for storage and maintenance of rates and reservations for thousands of hotels around the world.
Jeffrey Carpenter Systems Architect, Choice Hotels International
Jeff Carpenter is a software and systems architect with experience in the hospitality and defense industries, it. Jeff is currently working on a cloud-based hotel reservation system using Cassandra and is the author of the new O'Reilly book "Cassandra: The Definitive Guide, 2nd edition".
The Promise and Perils of Encrypting Cassandra Data (Ameesh Divatia, Baffle, ...DataStax
Why do data breaches occur even though we protect data at rest and in flight? What if the Cassandra admin's credentials get compromised? Why is it so hard to make encryption work for real world applications? If I encrypt my customer's data, do I have to turn it over when the authorities come calling? The answer may be in keeping data encrypted. . .always, let the customer own the keys and make data breaches irrelevant.
In this talk, Ameesh Divatia, Co-founder at Baffle.io, will talk about a way to encrypt individual fields in a Cassandra database while continuing to let them be available for CQL access. From deterministic to random algorithms, key management and integration into DataStax drivers, this talk will introduce attendees to the steps to follow in order to protect an existing Cassandra database with field-level granularity ensuring protection against data breaches.
About the Speaker
Ameesh Divatia President & CEO, Baffle, Inc.
Ameesh is a serial entrepreneur with over 25 years of operating experience in storage, security and networking infrastructure. He specializes in conceiving and implementing startup business plans that create new product categories by leveraging innovation in existing markets to its adjacencies. He co-founded Baffle in May 2015 to address the challenge of preventing data breaches in cloud infrastructure.
Tales From the Field: The Wrong Way of Using Cassandra (Carlos Rolo, Pythian)...DataStax
Cassandra is a distributed database with features included but not limited to Secundary Indexes, UDF, Materialized Views, etc. and not so strict hardware requirements.
It is important to use those features and select hardware correctly to make sure the use of Cassandra in your business can be as painless as possible.
I will address how these features are used in the wrong way, how hardware should be selected, and how to make Cassandra work in the best possible way.
Learning Objective #1:
Learn that Cassandra hardware requirements exist (and why) and the shortcomings in some of features(Secundary Indexes, Compaction Strategies, etc).
Learning Objective #2:
The most misused features and common hardware errors. How they might seem harmeless at first (either small cluster or even single node).
Learning Objective #3:
How to correctly use Cassandra and it's features and go for perfect operation.
About the Speaker
Carlos Rolo Cassandra Consultant, Pythian
Carlos Rolo is a Cassandra MVP, and has deep expertise with distributed architecture technologies. Carlos is driven by challenge, and enjoys the opportunities to discover new things.. He has become known and trusted by customers and colleagues for his ability to understand complex problems, and to work well under pressure. When Carlos isn't working he can be found playing water polo or enjoying the his local community.
Apache Cassandra operations have the reputation to be simple on single datacenter deployments and / or low volume clusters but they become way more complex on high latency multi-datacenter clusters with high volume and / or high throughout: basic Apache Cassandra operations such as repairs, compactions or hints delivery can have dramatic consequences even on a healthy high latency multi-datacenter cluster.
In this presentation, Julien will go through Apache Cassandra mutli-datacenter concepts first then show multi-datacenter operations essentials in details: bootstrapping new nodes and / or datacenter, repairs strategy, Java GC tuning, OS tuning, Apache Cassandra configuration and monitoring.
Based on his 3 years experience managing a multi-datacenter cluster against Apache Cassandra 2.0, 2.1, 2.2 and 3.0, Julien will give you tips on how to anticipate and prevent / mitigate issues related to basic Apache Cassandra operations with a multi-datacenter cluster.
About the Speaker
Julien Anguenot VP Software Engineering, iland Internet Solutions, Corp
Julien currently serves as iland's Vice President of Software Engineering. Prior to joining iland, Mr. Anguenot held tech leadership positions at several open source content management vendors and tech startups in Europe and in the U.S. Julien is a long time Open Source software advocate, contributor and speaker: Zope, ZODB, Nuxeo contributor, Zope and OpenStack foundations member, his talks includes Apache Con, Cassandra summit, OpenStack summit, The WWW Conference or still EuroPython.
Every company likes to brag about their successes, but not many are willing to talk about their failures. At PagerDuty we have been rigorously tracking downtime in order to analyze it and learn from our mistakes - we even blog about these failures publicly.
Despite being a highly available system, we have had three outages caused by problems with our production Cassandra clusters over the past year. We'll take a look at each of these outages: what we saw from the inside, the actions we took to recover, and most importantly the procedures and monitoring that will help prevent it from happening to you.
Maintaining Consistency Across Data Centers (Randy Fradin, BlackRock) | Cassa...DataStax
We use Apache Cassandra at BlackRock to help power our Aladdin investment management platform. Like most users, we love Cassandra’s scalability and fault tolerance. One challenge we’ve faced is keeping data consistent between data centers. Cassandra is great at replicating data to multiple data centers, and many users take advantage of this feature to achieve eventual consistency in multi-region clusters. At BlackRock, we have several use cases where eventual consistency is not good enough; sometimes we need to guarantee that the most recent data is available from all locations. Cassandra’s tunable consistency makes it possible to achieve this extreme level of resiliency. In this talk we’ll discuss our experience from the past several years using Cassandra for cross-WAN consistency, some of the novel ways we’ve dealt with the performance implications, and our ideas for improving support for this usage model in future versions of Cassandra.
About the Speaker
Randy Fradin Vice President, BlackRock
Randy Fradin is part of BlackRock’s Aladdin Product Group. His team is responsible for developing the core software infrastructure in BlackRock’s Aladdin platform, including scalable storage, compute, and messaging services. Previously he spent time developing the market data, risk reporting, and core trading functions in Aladdin. He has been an enthusiastic Cassandra user since 2011.
Operations, Consistency, Failover for Multi-DC Clusters (Alexander Dejanovski...DataStax
Cassandra's support for multiple data centers can bring massive benefits to an organization, however it can also bring painful operational lessons. While there is no recipe for trouble free mutli DC clusters, the best approach is to understand why you are using one, what Cassandra supports, and how it does it. With this knowledge in your toolkit you will have a better chance of fixing the sort of gremlins that can trouble a globally distributed database.
In this talk Alexander Dejanovski, Consultant at The Last Pickle, will outline the motivations people typically have for running a multi DC cluster. He will also look at how multiple DC's are supported through all areas of the Cassandra, how it impacts your application and operations, and how you can always blame the network.
About the Speaker
Alexander DEJANOVSKI Consultant, The Last Pickle
Alexander has been working as a software developer for the last 18 years, mainly for the french leader of express shipments. He's been leading there the effort to build a Cassandra based architecture and migrate services to it from traditional RDBMS. He is involved in the Cassandra community through the development of a JDBC wrapper for the DataStax Java Driver. Recently, he joined The Last Pickle as a Cassandra consultant and now helps customers to get the best out of it.
Always On: Building Highly Available Applications on CassandraRobbie Strickland
Cassandra was built from the ground up to enable linearly scalable, always-on applications. But the path to high availability has many land mines that can mean failure for the inexperienced user. In this talk, I will offer practical advice on how to achieve 100% uptime on millions of transactions per second. I'll address all aspects of the topic, including deployment, configuration, application design, and operations.
SRV402 Deep Dive on Amazon EC2 Instances, Featuring Performance Optimization ...Amazon Web Services
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and Accelerated Computing (GPU and FPGA) instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Using Time Window Compaction Strategy For Time Series WorkloadsJeff Jirsa
Cassandra is a great fit for high write use cases, which makes it a popular choice for storing time series and sensor-collection workloads. At Crowdstrike, we've been using Cassandra for just that purpose, collecting petabytes of expiring time series data. In this talk, I'll discuss compaction in time series workloads, and the TimeWindowCompactionStrategy we developed specifically for this purpose. I'll detail TWCS specific configuration properties, some lesser known compaction sub-properties that apply to all compaction strategies, and also cover other general tricks and tuning that are useful for very large time-series workloads.
QuestDB: The building blocks of a fast open-source time-series databasejavier ramirez
(talk delivered at OSA CON 23)
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed.
We will learn how it deals with data ingestion, and which SQL extensions it implements for working with time-series efficiently.
We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or data deduplication.
SRV402 Deep Dive on Amazon EC2 Instances, Featuring Performance Optimization ...Amazon Web Services
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and Accelerated Computing (GPU and FPGA) instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
SRV402 Deep Dive on Amazon EC2 Instances, Featuring Performance Optimization ...Amazon Web Services
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and Accelerated Computing (GPU and FPGA) instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
The introduction of DateTieredCompactionStrategy in late 2014 was a significant step forward in providing a viable compaction strategy for time series data, especially time series data that will be TTL'd out. DateTieredCompactionStrategy's introduction was met with genuine excitement, and its rapid adoption is testament to developers' and operators' desire to have data compacted in a way that better matches their write patterns.
However, DateTieredCompactionStrategy's features come with significant limitations. This talk will review our real world benchmarking and use cases for DTCS as a vehicle to discuss the implications of DateTieredCompactionStrategy on operational tasks such as repair, read-repair, bootstrapping, and especially DR recovery scenarios, and it will also discuss how those various limitations lead us to proposing an operations-friendly alternative to DateTieredCompactionStrategy.
Some vignettes and advice based on prior experience with Cassandra clusters in live environments. Includes some material from other operational slides.
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Instaclustr has a diverse customer base including Ad Tech, IoT and messaging applications ranging from small start ups to large enterprises. In this presentation we share our experiences, common issues, diagnosis methods, and some tips and tricks for managing your Cassandra cluster.
About the Speaker
Brooke Jensen VP Technical Operations & Customer Services, Instaclustr
Instaclustr is the only provider of fully managed Cassandra as a Service in the world. Brooke Jensen manages our team of Engineers that maintain the operational performance of our diverse fleet clusters, as well as providing 24/7 advice and support to our customers. Brooke has over 10 years' experience as a Software Engineer, specializing in performance optimization of large systems and has extensive experience managing and resolving major system incidents.
Building an Amazon Datawarehouse and Using Business Intelligence Analytics ToolsAmazon Web Services
Using AWS has never been easier or more affordable to solve business problems and uncover new opportunities using data. Now, businesses of all sizes and across all industries can take advantage of big data technologies and easily collect, store, process, analyze, and share their data. Gain a thorough understanding of what AWS offers across the big data lifecycle and learn architectural best practices for applying these technologies to your projects. We will also deep dive into how to use AWS services such as Kinesis, DynamoDB, Redshift, and Quicksight to optimize logging, build real-time applications, and analyze and visualize data at any scale.
Cómo se diseña una base de datos que pueda ingerir más de cuatro millones de ...javier ramirez
En esta sesión voy a contar las decisiones técnicas que tomamos al desarrollar QuestDB, una base de datos Open Source para series temporales compatible con Postgres, y cómo conseguimos escribir más de cuatro millones de filas por segundo sin bloquear o enlentecer las consultas.
Hablaré de cosas como (zero) Garbage Collection, vectorización de instrucciones usando SIMD, reescribir en lugar de reutilizar para arañar microsegundos, aprovecharse de los avances en procesadores, discos duros y sistemas operativos, como por ejemplo el soporte de io_uring, o del balance entre experiencia de usuario y rendimiento cuando se plantean nuevas funcionalidades.
Observer, a "real life" time series applicationKévin LOVATO
Time series examples are often seen in the Cassandra literature, but how do we deal with them in real life applications, outside of the usual "weather station" example?
We have been building and perfecting our own metrics system for over a year and we will share what we've learned, from schema design to data access optimization.
Performance Analysis: new tools and concepts from the cloudBrendan Gregg
Talk delivered at SCaLE10x, Los Angeles 2012.
Cloud Computing introduces new challenges for performance
analysis, for both customers and operators of the cloud. Apart from
monitoring a scaling environment, issues within a system can be
complicated when tenants are competing for the same resources, and are
invisible to each other. Other factors include rapidly changing
production code and wildly unpredictable traffic surges. For
performance analysis in the Joyent public cloud, we use a variety of
tools including Dynamic Tracing, which allows us to create custom
tools and metrics and to explore new concepts. In this presentation
I'll discuss a collection of these tools and the metrics that they
measure. While these are DTrace-based, the focus of the talk is on
which metrics are proving useful for analyzing real cloud issues.
If you're building relational, time-series, IOT, or real-time architectures using Hadoop, you will find Apache Kudu an attractive choice. With Kudu, you'll be able to build your applications more simply and with fewer moving parts.
Hadoop has become faster and more capable, and has continued to narrow the gap compared to traditional database technologies. However, for developers looking for up-to-the-second analytics on fast-moving data, some important gaps remain that prevent many applications from transitioning to Hadoop-based architectures. Users are often caught between a rock and a hard place: columnar formats such as Apache Parquet offer extremely fast scan rates for analytics, but little to no ability for real-time modification or row-by-row indexed access. Online systems such as HBase offer very fast random access, but scan rates that are too slow for large scale data warehousing and analytical workloads.
This talk will describe Kudu, the new addition to the open source Hadoop ecosystem with out-of-the-box integration with Apache Spark and Apache Impala. Kudu fills the gap described above to provide a new option to achieve fast scans and fast random access from a single API.
Similar to Terror & Hysteria: Cost Effective Scaling of Time Series Data with Cassandra (Sam Bisbee, Threat Stack) | C* Summit 2016 (20)
Is Your Enterprise Ready to Shine This Holiday Season?DataStax
Be a holiday hero—not a sorry statistic. View this on-demand webinar to learn how to drive revenue, business growth, customer satisfaction, and loyalty during the holiday season, and achieve operational excellence (and sanity!) at the same time. You’ll also hear real-world stories of companies that have experienced Black Friday nightmares—and learn how they turned things back around.
View webinar: https://pages.datastax.com/20191003-NAM-Webinar-IsYourEnterpriseReadytoShinethisHolidaySeason_1-Registration-LP.html
Explore all DataStax webinars: www.datastax.com/webinars
Designing Fault-Tolerant Applications with DataStax Enterprise and Apache Cas...DataStax
Data resiliency and availability are mission-critical for enterprises today—yet we live in a world where outages are an everyday occurrence. Whether the problem is a single server failure or losing connectivity to an entire data center, if your applications aren’t designed to be fault tolerant, recovery from an outage can be painful and slow. Watch this on-demand webinar to look at best practices for developing fault-tolerant applications with DataStax Drivers for Apache Cassandra and DataStax Enterprise (DSE).
View recording: https://youtu.be/NT2-i3u5wo0
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Running DataStax Enterprise in VMware Cloud and Hybrid EnvironmentsDataStax
To simplify deploying and managing modern applications, enterprises have been combining the benefits of hyperconverged infrastructure (HCI) with the performance and scale of a NoSQL database — and the results have been remarkable. With this combination, IT organizations have experienced more agility, improved reliability, and better application performance. Watch this on-demand webinar where you’ll learn specifically how VMware HCI with DataStax Enterprise (DSE) and Apache Cassandra™ are transforming the enterprise.
View recording: https://youtu.be/FCLGHMIB0L4
Explore all DataStax Webinars: https://www.datastax.com/resources/webinars
Best Practices for Getting to Production with DataStax Enterprise GraphDataStax
A distributed graph database is the most powerful means of discovering and leveraging the relationships in your data. With the right techniques combined with the right enterprise graph features, you can build modern applications at scale for real-time use-cases. But how exactly should you manage and model your data for a distributed graph database? And how can you leverage the relationships in that data? Watch this on-demand webinar as our graph expert answers those questions and shares tips and insights into creating production apps with distributed graph data.
View recording: https://youtu.be/TSs_qPnhOas
Webinar | Data Management for Hybrid and Multi-Cloud: A Four-Step JourneyDataStax
Data management may be the hardest part of making the transition to the cloud, but enterprises including Intuit and Macy’s have figured out how to do it right. So what do they know that you might not? Join Robin Schumacher, Chief Product Officer at DataStax as he explores best practices for defining and implementing data management strategies for the cloud. He outlines a four-step journey that will take you from your first deployment in the cloud through to a true intercloud implementation and walk through a real-world use case where a major retailer has evolved through the four phases over a period of four years and is now benefiting from a highly resilient multi-cloud deployment.
View webinar: https://youtu.be/RrTxQ2BAxjg
Webinar | How to Understand Apache Cassandra™ Performance Through Read/Writ...DataStax
In this webinar, you will leverage free and open source tools as well as enterprise-grade utilities developed by DataStax to get a solid grasp on the performance of a masterless distributed database like Cassandra. You’ll also get the opportunity to walk through DataStax Enterprise Insights dashboards and see exactly how to identify performance bottlenecks.
View Recording: https://youtu.be/McZg_MMzVjI
Webinar | Better Together: Apache Cassandra and Apache KafkaDataStax
In this webinar, you’ll also be introduced to DataStax Apache Kafka Connector, and get a brief demonstration of this groundbreaking technology. You’ll directly experience how this tool can help you stream data from Kafka topics into DataStax Enterprise versions of Cassandra. The future of your organization won’t wait. Register now to reserve your spot in this exciting new webinar.
Youtube: https://youtu.be/HmkNb8twUNk
Top 10 Best Practices for Apache Cassandra and DataStax EnterpriseDataStax
No matter how diligent your organization is at driving toward efficiency, databases are complex and it’s easy to make mistakes on your way to production. The good news is, these mistakes are completely avoidable. In this webinar, Jeff Carpenter shares with you exactly how to get started in the right direction — and stay on the path to a successful database launch.
View recording: https://youtu.be/K9Zj3bhjdQg
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Introduction to Apache Cassandra™ + What’s New in 4.0DataStax
Apache Cassandra has been a driving force for applications that scale for over 10 years. This open-source database now powers 30% of the Fortune 100.Now is your chance to get an inside look, guided by the company that’s responsible for 85% of the code commits.You won’t want to miss this deep dive into the database that has become the power behind the moment — the force behind game-changing, scalable cloud applications - Patrick McFadin, VP Developer Relations at DataStax, is going behind the Cassandra curtain in an exclusive webinar.
View recording: https://youtu.be/z8fLn8GL5as
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Webinar: How Active Everywhere Database Architecture Accelerates Hybrid Cloud...DataStax
In this webinar, we’ll discuss how an Active Everywhere database—a masterless architecture where multiple servers (or nodes) are grouped together in a cluster—provides a consistent data fabric between on-premises data centers and public clouds, enabling enterprises to effortlessly scale their hybrid cloud deployments and easily transition to the new hybrid cloud world, without changes to existing applications.
View recording: https://youtu.be/ob6tr-9YiF4
Webinar | Aligning GDPR Requirements with Today's Hybrid Cloud RealitiesDataStax
The European Union’s General Data Protection Regulation (GDPR) has sweeping effects on how enterprises manage their data. Without the right policies and safeguards in place, a tiny data mishap could end up turning into a catastrophic mistake. Join Datastax and our partner Thales eSecurity for a live webinar to learn how GDPR effects impact data management and the various ways enterprises can both comply and thrive in a hybrid cloud environment.
View recording: https://youtu.be/QZ48_qkK9PU
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Designing a Distributed Cloud Database for DummiesDataStax
Join Designing a Distributed Cloud Database for Dummies—the webinar. The webinar “stars” industry vet Patrick McFadin, best known among developers for his seven years at Apache Cassandra, where he held pivotal community roles. Register for the webinar today to learn: why you need distributed cloud databases, the technology you need to create the best used experience, the benefits of data autonomy and much more.
View the recording: https://youtu.be/azC7lB0QU7E
To explore all DataStax webinars: https://www.datastax.com/resources/webinars
How to Power Innovation with Geo-Distributed Data Management in Hybrid CloudDataStax
Most enterprises understand the value of hybrid cloud. In fact, your enterprise is already working in a multi-cloud or hybrid cloud environment, whether you know it or not. View this SlideShare to gain a greater understanding of the requirements of a geo-distributed cloud database in hybrid and multi-cloud environments.
View recording: https://youtu.be/tHukS-p6lUI
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
How to Evaluate Cloud Databases for eCommerceDataStax
View these slides to discover the advantages of a distributed cloud database designed for hybrid cloud along with examples of how companies are delivering innovative and personalized ecommerce experiences. We'll discuss the sources of common data challenges and the hidden impact they have on business, the database requirements for improved customer experiences and innovative application delivery, and how leading organizations such as eBay, Sony, Macy’s, and Comcast are transforming the eCommerce experience with DataStax Enterprise 6.
View recording: https://youtu.be/4UXrJ3xtmGg
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Webinar: DataStax Enterprise 6: 10 Ways to Multiply the Power of Apache Cassa...DataStax
Today’s customers want experiences that are contextual, always on, and above all — delightful. To be able to provide this, enterprises need a distributed, hybrid cloud-ready database that can easily crunch massive volumes of data from disparate sources while offering data autonomy and operational simplicity. Don’t miss this webinar, where you’ll learn how DataStax Enterprise 6 maintains hybrid cloud flexibility with all the benefits of a distributed cloud database, delivers all the advantages of Apache Cassandra with none of the complexities, doubles performance, and provides additional capabilities around robust transactional analytics, graph, search, and more.
View recording: https://youtu.be/tuiWAt2jwBw
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Webinar: DataStax and Microsoft Azure: Empowering the Right-Now Enterprise wi...DataStax
Today’s Right-Now Economy means employees and customers alike expect applications to be always on, real time, and contextual. But how do you manage applications that collect data from a variety of sources, at cloud scale, and provide instant insights? And, can you embrace the public cloud while still retaining control of your data? Join us to hear from Microsoft Cloud Architect and Azure Global Black Belt Ron Abellera to learn how an enterprise-ready hybrid cloud data layer can help to accelerate time to market and scale linearly, ensure continuous availability, and achieve data autonomy with a hybrid cloud strategy.
View webinar recording: https://youtu.be/_-GqmAk5C_I
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Webinar - Real-Time Customer Experience for the Right-Now Enterprise featurin...DataStax
Welcome to the Right-Now Economy. To win in the Right-Now Economy, your enterprise needs to be able to provide delightful, always-on, instantaneously responsive applications via a data layer that can handle data rapidly, in real time, and at cloud scale. Don’t miss our upcoming webinar in which Forrester Principal Analyst Brendan Witcher will discuss why a singular, contextual, 360-degree view of the customer in real-time is critical to CX success and how companies are using data to deliver real-time personalization and recommendations.
View recording: https://youtu.be/e6prezfIGMY
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Datastax - The Architect's guide to customer experience (CX)DataStax
From scalability to data access to data governance, learn the specific performance and data requirements of a customer experience-ready data management platform.
An Operational Data Layer is Critical for Transformative Banking ApplicationsDataStax
Customer expectations are changing fast, while customer-related data is pouring in at an unprecedented rate and volume. Join this webinar, to hear leading experts from DataStax, discuss how DataStax Enterprise, the data management platform trusted by 9 out of the top 15 global banks, enables innovation and industry transformation. They’ll cover how the right data management platform can help break down data silos and modernize old systems of record as an operational data layer that scales to meet the distributed, real-time, always available demands of the enterprise. Register now to learn how the right data management platform allows you to power innovative banking applications, gain instant insight into comprehensive customer interactions, and beat fraud before it happens.
Video: https://youtu.be/319NnKEKJzI
Explore all DataStax webinars: https://www.datastax.com/resources/webinars
Becoming a Customer-Centric Enterprise Via Real-Time Data and Design ThinkingDataStax
Customer expectations are changing fast, while customer-related data is pouring in at an unprecedented rate and volume. How can you contextualize and analyze all this customer data in real time to meet increasingly demanding customer expectations? Join Mike Rowland, Director and National Practice Leader for CX Strategy at West Monroe Partners, and Kartavya Jain, Product Marketing Manager at DataStax, for an in-depth conversation about how customer experience frameworks, driven by Design Thinking, can help enterprises: understand their customers and their needs, define their strategy for real-time CX, create value from contextual and instant insights.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
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In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Terror & Hysteria: Cost Effective Scaling of Time Series Data with Cassandra (Sam Bisbee, Threat Stack) | C* Summit 2016
1. Terror & Hysteria: Cost Effective
Scaling of Time Series Data
with Cassandra
Sam Bisbee, Threat Stack CTO
2. Typical [time series] problems on C*
● Disk utilization creates a scaling pattern of lighting money on
fire
– Only works for a month or two, even with 90% disk utilization
● Every write up we found focused on schema design for
tracking integers across time
– There are days we wish we only tracked integers
● Data drastically loses value over time, but C*'s design
doesn't acknowledge this
– TTLs only address 0 value states, not partial value
– Ex., 99% of reads are for data in its first day
● Not all sensors are equal
3. Categories of Time Series Data
Volume of Tx's
Size of Tx's
CRUD, Web 2.0
System Monitoring
(CPU, etc.)
System Monitoring
(CPU, etc.)
Traditional object store
Threat Stack
4. Categories of Time Series Data
Volume of Tx's
Size of Tx's
CRUD, Web 2.0
System Monitoring
(CPU, etc.)
System Monitoring
(CPU, etc.)
Traditional object store
Threat Stack
Traditional time
series on C*, what
everyone writes about
“We're going to need
a bigger boat. Or disks.”
5. We care about this thing called margins
(see: we're in Boston, not the Valley)
6. Data at Threat Stack
● 5 to 10TBs per day of raw data
– Crossed several TB per day in first few months of production with ~4 people
● 80,000 to 150,000 Tx per second, analyzed in real time
– Internal goal of analyzing, persisting, and firing alerts in <1s
● 90% write to 10% read tx
● Pre-compute query results for 70% of queries for UI
– Optimized lookup tables & complex data structures, not just “query & cache”
● 100% AWS, distrust of remote storage in our DNA
– This is not just EBS bashing. This applies to all databases on all platforms,
even a cage in a data center.
● By the way, we're on DSE 4.8.4 (C* 2.1)
7. Generic data model
● Entire platform assumes that events form a partially ordered, eventually
consistent, write ahead log
– A wonderful C* use case, so long as you only INSERT
● UPDATE is a dirty word and C* counters are “banned”
– We do our big counts elsewhere (“right tool for the right job”)
● No DELETEs, too many key permutations and don't want tombstones
● Duplicate writes will happen
– Legitimate: fully or partially failed batches of writes
– Legitimate: sensor resends data because it doesn't see platform's
acknowledgement of data
– How-do-you-even-computer: people cannot configure NTP, so have fun
constantly receiving data from 1970
● TTL on insert time, store and query on event time
8. We need to show individual events or slices,
cannot use time granularity rows
(1min, 15min, 30min, 1hr, etc.)
9. Creating and updating tables' schema
● ALTER TABLE isn't fun, so we support dual writes instead
– Create new schema, performing dual reads for new & old
– Cut writes over to new schema
– After TTL time, DROP TABLE old
● Each step is verifiable with unit tests and metrics
● Maintains insert only data model for temporary disk util
cost
● Allows trivial testing of analysis and A/B'ing of schema
– Just toss a new schema in, gather some insights, and then
feel free to drop it
10. AWS Instance Types & EBS
● EBS is generally banned on our platform
– Too many of us lived through the great outage
– Too many of us cannot live with unpredictable I/O patterns
– Biggest reason: you cannot RI EBS
● Originally used i2.2xlarge's in 2014/2015
– Considering amount of “learning” we did, we were very
grateful for SSDs due to amount of streaming we had to do
● Moved to d2.xlarge's and d2.2xlarge's in 2015
– RAID 0 the spindles with xfs
– We like the CPU and RAM to disk ratio, especially since
compaction stops after a few hours
11. $/TB on AWS
i2.2xlarge d2.2xlarge c3.2xlarge +
6 x 2TB io1 EBS
No Prepay $619.04 / 1.6TB
= $386 / TB / month
$586.92 / 12TB
= $49.91 / TB / month
$1,713.16 / 12TB
= $142.77/TB/month
Partial Prepay $530.37 / 1.6TB
= $331.48/TB/month
$502.12 / 12TB
= $41.85 / TB / month
$1,684.59 / 12TB
= $140.39/TB/month
Full Prepay $519.17 / 1.6TB
= $324.85/TB/month
$492 / 12TB
= $41 / TB / month
$1,680.84 / 12TB
= $140.07/TB/month
● Amortizes one-time RI across 1yr, focusing on cost instead of cash out of
pocket
● Does not account for N=3 in cluster, so x3 for each record, then x2 for worst
case compaction headroom (realistically need MUCH LESS)
● c3 column assumes d2 comparison on disk size, not fair versus i2
12. We only store some raw data in C*
● Deleting data proved too difficult in the early days, even
with DTCS (slides coming on how we solved this)
● Re-streaming due to regular maintenance could take a
week or more
– Dropping instance size doesn't solve throughput problem
since all resources are cut, not just disk size
– Another reason not to use EBS since you'll “never” get close
to 100% disk utilization
● Due to aforementioned C* durability design, cost of data
for day 2..N is too high even if you drop replica count
13. Tying C* to raw data
● Every query must constrain a minimum of:
– Sensor ID
– Event Day
● Every query result must include a minimum of:
– Sensor ID
– Event Day
– Event ID
● Batches of (sensor_id, event_day, event_id) triples are
then used to look up the raw events from raw data storage
– This isn't always necessary (aggregates, correlations, etc.)
– Even with additional hops, full reads are still <1s
14. Using triples to batch writes
● Partition key starts with sensor id and event day
– Bonus: you get fresh ring location every day! Helps for
averaging out your schema mistakes over the TTL
● Event batches off of RabbitMQ are already constrained to
a single sensor id and event day
– Allows mapping a single AMQP read to a single C* write
(RabbitMQ is podded, not clustered)
– Flow state of pipeline becomes trivial to understand
● Batch C* writes on partition key, then data size (soft cap at
5120 bytes, C* inner warn)
15. Compaction woes, STCS & DTCS
● Used STCS in 2014/2015, expired data would get stuck ∞
– “We could rotate tables” → eh, no
– “We could rotate clusters” → oh c'mon, hell no
– “We could generate every historic permutation of keys within
that time bucket with Spark and run DELETEs” →...............
● Used DTCS in 2015, but expired data still got stuck ∞
– When deciding whether an SSTable is too old to compact,
compares “now” versus max timestamp (most recent write)
– If you write constantly (time series), then SSTables will rarely
or never stop compacting
– This means that you never realize the true value of DTCS for
time series, the ability to unlink whole SSTables from disk
16. Cluster disk states assuming const sensor count
Disk Util
Time
What you want
What you get
Initial build up to
retention period
18. MTCS settings
● Never run repairs (never worked on STCS or DTCS anyway)
and hinted handoff is off (great way to kill a cluster anyway)
● max_sstable_age_days = 1
base_time_seconds = 1 hour
● Results in roughly hour bucket sequential SSTables
– Reads are happy due to day or hour resolution, which have to
provide this in the partition key anyway
● Rest of DTCS sub-properties are default
● Not worried about really old and small SSTables since those
are simply unlinked “soon”
19. MTCS + sstablejanitor.sh
● Even with MTCS, SSTables were still not getting unlinked
● So enters sstablejanitor.sh
– Cron job fires it once per hour
– Iterates over each SSTable on disk for MTCS tables (chef/cron
feeds it a list of tables and their TTLs)
– Uses sstablemetadata to determine max timestamp
– If past TTL, then uses JMX to invoke CompactionManager's
forceUserDefinedCompaction on the table
● Hack? Yes, cron + sed + awk + JMX qualifies as a hack, but
it works like a charm and we don't carry expired data
● Bonus: don't need to reserve half your disks for compaction