Cassandra at Glogster
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Roman Komkov presented on Cassandra at Glogster. Glogster EDU is an online platform used by 19 million users for presentation and learning, generating over 45,000 new projects daily. Glogster has used Cassandra since 2011 as its primary database, starting with 0.6-0.8 and upgrading over time. Currently it uses a 5 node cluster storing 600GB of data. Upgrades brought challenges around migration, repairs, and a data loss incident that took 10 days to repair after decommissioning an old datacenter without proper hints handling. Lessons included increasing repair windows, enabling parallel repairs, and regularly scheduling backups and repairs.
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Javi
El documento describe las cuatro libertades principales del software libre: 1) la libertad de usar el programa con cualquier propósito, 2) la libertad de estudiar y modificar el código, 3) la libertad de distribuir copias, y 4) la libertad de distribuir versiones modificadas.
SC=DCPP Final Report=JA= 29-7-2012
This document summarizes a situation analysis conducted by Save the Children on the children of sex workers in and around the Daulatdia brothel in Bangladesh. Key findings include:
1) The Daulatdia Child Protection Program aims to develop community-supported child protection systems within the brothel, which faces issues like corruption, violence, drug/alcohol use, and the promotion of child sex work. Mothers lack knowledge to protect their children.
2) The analysis assessed the socio-demographic backgrounds, views on Save the Children's program and local dynamics, and the role of organizations in ensuring child protection of children of sex workers, as well as their access to health, education, security and recreation.
Equity Risk Premium in an Emerging Market Economy
The finance literature suggests that in almost any kind of investing, returns would at least have some
relationship with risk-free rate of return (Rf), with investors demanding higher returns for greater risk. Risk-free
asset is regarded as one where the investor knows the expected return with certainty. This leads to the notion of
Equity Risk Premium (ERP), the extra return that, as compensation for the additional borne risk, the investor
earns over the Rf
, typically taken as 91-day Treasury bills (TB) rate of return. While similar studies have been
performed in the past, the applicability of the ERP concept across financial markets and its economic
implications as a risk measure has remained a contentious issue in the field, particular in emerging markets.
The present study seeks to revisit the issue in the Nigerian context based on secondary data spanning 2000-
2011. The statistical analysis based on the capital asset pricing model shows that the country’s Rf proxied by
TBs, had over the years traded at significantly higher levels of return than obtainable from market portfolio,
thus creating a negative ERP phenomenon. The implications of this peculiarity for sustainable wealth creation,
business development and valuation practice, are highlighted. Recent changes in the country’s Administration
makes this study even more relevant, thus, the paper also renews the call for creating a more pro-industry fiscal
policy climate if the national aspiration for sustainable inclusive growth is to be attained.
Aspergillus terrreus
The document summarizes research characterizing gold nanoparticles synthesized intracellularly by the biomass of Aspergillus terreus fungus. When an aqueous solution of chloroauric acid was reduced by A. terreus biomass, it changed color from yellow to pinkish violet, indicating gold nanoparticle formation. The synthesized nanoparticles were spherical or irregularly shaped with an average size of 186 nm. Fourier transform infrared spectroscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy and X-ray diffraction were used to characterize the nanoparticles and confirmed the presence of crystalline gold nanoparticles capped by biomolecules from the fungus.
ALI IRTIZA 13-01-2016(1)
This curriculum vitae provides personal and professional details for Ali Irtiza. He is a retired engine technician from the Pakistan Air Force seeking a challenging career in aviation. He has extensive experience maintaining and overhauling aircraft engines including the ATAR 09C5, P&W (F-16), and CFM56-3C. He has also worked as an aerospace technician for Boeing 737-400 and Airbus 320 aircraft.
iPECS Solution Poster No.1
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Tarea del seminario 3
El documento describe la tarea de realizar una investigación sobre el tratamiento quirúrgico del glaucoma y las cataratas publicado en España desde 2010. Instruye buscar en al menos una base de datos en castellano y localizar el texto completo de dos documentos encontrados que no estén disponibles en la base de datos. Proporciona la estrategia de búsqueda utilizada en Dialnet y el proceso para acceder al texto completo de dos artículos a través del catálogo Fama+ de la Biblioteca de Centros de Salud de la Universidad de Sevilla.
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This document summarizes the work done to set up a computing cluster at Florida Tech. It describes installing Rocks on a frontend server and nodes, setting up Condor as the batch job system, and using OpenFiler for network attached storage. The cluster originally had one frontend and one compute node from the University of Florida. Future work involves recovering from a hard drive failure on the frontend and continuing the installation of the Open Science Grid.
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In the last decade, the development of modern horizontally scalable open-source Big Data technologies such as Apache Cassandra (for data storage), and Apache Kafka (for data streaming) enabled cost-effective, highly scalable, reliable, low-latency applications, and made these technologies increasingly ubiquitous. To enable reliable horizontal scalability, both Cassandra and Kafka utilize partitioning (for concurrency) and replication (for reliability and availability) across clustered servers. But building scalable applications isn’t as easy as just throwing more servers at the clusters, and unexpected speed humps are common. Consequently, you also need to understand the performance impact of partitions, replication, and clusters; monitor the correct metrics to have an end-to-end view of applications and clusters; conduct careful benchmarking, and scale and tune iteratively to take into account performance insights and optimizations. In this presentation, I will explore some of the performance goals, challenges, solutions, and results I discovered over the last 5 years building multiple realistic demonstration applications. The examples will include trade-offs with elastic Cassandra auto-scaling, scaling a Cassandra and Kafka anomaly detection application to 19 Billion checks per day, and building low-latency streaming data pipelines using Kafka Connect for multiple heterogeneous source and sink systems.
Exascale Capabl
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2. Moving data is a major challenge, as moving data off-chip uses 200x more energy than computing with it on-chip.
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Cassandra To Infinity And Beyond
How Teads scale with Apache Cassandra.
Internet scale means tons of data, read heavy workload, massive data ingestion and low latency.
The French AdTech company Teads uses Cassandra massively, a reliable and performant Open Source database.
Spawning Cassandra nodes in AWS is a piece of cake with Terraform and Chef.
Multi-cluster k8ssandra
Presented by Rags Srinivas, Developer Advocate/Architect at Datastax at Kubernetes Community Days, Washington DC, September 14, 2022.
Cassandra is designed for multi-region
● Partition tolerant
● Each node in the cluster maintains the full topology
● Nodes automatically route traffic to nearby neighbors
● Data is automatically and asynchronously replicated
● The cluster is homogenous
● Any node can service any client request
● Clients can be configured to automatically route traffic to the local datacenter
Kubernetes was not designed for multi-region
● Increased latencies
● The cost is higher consensus request latency from crossing data center boundaries
● Loss of connectivity to ectd could cause outages
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Programmable Exascale Supercomputer
We leave in the era where the atomic building elements of silicon computers, e.g., transistors and wires, are no longer visible using traditional optical microscopes and their sizes are measured in just tens of Angstroms. In addition, power dissipation per unit volume is bounded by the laws of Physics that all resulted among others in stagnating processor clock frequencies. Adding more and more processor cores that perform simpler and simpler tasks in an attempt to efficiently fill the available on-chip area seems to be the current trend taken by the Industry.
S3, Cassandra or Outer Space? Dumping Time Series Data using Spark - Demi Be...
The document discusses time series data processing using Apache Spark. It begins with an introduction of the speaker and an overview of Spark. It then describes the structure and flow of maritime location data. The challenges of processing this streaming time series data are discussed, including delays in data arrival that can cause holes in computations. The document outlines the evolution of their solution from using MongoDB to using Apache Spark with Cassandra and S3 for improved performance and scalability. It concludes with lessons about understanding data characteristics and choosing the right persistence layers.
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Cassandra at Glogster
- 1. Cassandra at Glogster Roman Komkov – roman@glogster.com System Engineer at Glogster Prague Cassandra Meet up 03.09.2015
- 2. About me 2 years at Glogster EDU as System Engineer 5+ years of Linux administration 5+ years of Python development Cluster, HA, Orchestration CI, CD… Twitter - @alkoengineering GitHub, Freenode - decayofmind
- 3. About Glogster EDU Started in 2009 Platform for presentation and interactive learning mainly used by educators and students 19 million users Over 45 million glogs 40000 new glogs daily Web service, mobile applications http://edu.glogster.com
- 4. Cassandra at Glogster From 2011 as primary DB for initial Glogster.com From 2012 as backend (storage) DB for Glogster EDU Started from 0.6… or 0.8, I guess… 10 nodes RF=5, QUORUM SATA disks OrderPreservingPartitioner ¯_(ツ)_/¯
- 5. Architecture
- 6. Cassandra now 5 nodes cluster ~600Gb average node size RF=5, QUORUM SSD disks VNodes OrderPreservingPartitioner… pycassa + datastax-driver
- 8. 0.8 problems Migration with downtime by transferring a copy of data HintedHandoff hell No repairs, no cleanups Enormous HeapSize (20GB) Different time on servers SOLUTION! Upgrade to 1.0
- 9. 1.1 problems Cassandra guy left Glogster Don’t touch it while it works BUT… Load averages like 14.0-16.0 2 disks failed Everything is slow Repairs? Never heard!
- 10. 1.1 solutions Replace disks, rebuild nodes. Don’t try to run repair on new node instead of ReplaceToken Move old Glogster.com keyspace to another cluster Load gone https://glogster.github.io/posts/2015/03/23/cassandra- migration.html Nodes are fast again Regular repairs and cleanups? Never did! OpsCenter installed Cluster upgraded to 1.2
- 11. 1.2 and migration Cluster migrated to the new servers without downtime http://www.planetcassandra.org/blog/cassandra-migration- to-ec2/ Vnodes …
- 13. Old datacenter, connected to production was disconnected from new datacenter Forgot about Hints TTL (max_hint_window_in_ms ~ 3 hours) Forgot to run repair on cluster after Old DC was decommissioned Application switched the new one … DATA GONE
- 14. Here the hell begins ~ 1200 glogs remain on old decommissioned datacenter Thanks God, we have RF=<N of nodes> Transfer data from one old node to the new server Run Cassandra on it, add node to the cluster Run repair on entire cluster Increase repair chance with read_repair_chance Peacefully wait until done… Do your complicated repairs through OpsCenter, cause it can continue if failed.
- 15. Full repair?
- 17. 10 DAYS!!!
- 18. Conclusions and Improvements Increase max_hint_window_in_ms value to something like 3 days Make use of parallel things CQL3 and datastax-driver Upgrade to Cassandra 2.2 faster repairs and other operations New OpsCenter Schedule regular backups and repairs We still love Cassandra!
- 19. Questions?