Have you ever wondered what the relative differences are between two of the more popular open source, in-memory data stores and caches? In this session, we will describe those differences and, more importantly, provide live demonstrations of the key capabilities that could have a major impact on your architectural Java application designs.
Ontology development in protégé-آنتولوژی در پروتوغهsadegh salehi
This document describes an agenda for an ontology development presentation in Protégé. It discusses the syntactic web and its limitations, as well as the promise of the semantic web to address these issues by adding meaning to web content that is understandable to machines. It outlines two sessions on ontology and OWL basics, Protégé, and developing a pizza ontology in Protégé.
Ranger provides centralized authorization policies for Hadoop resources. A new Ranger Hive Metastore security agent was introduced to address gaps in authorizing Hive CLI and synchronizing policies with object changes. It enforces authorization for Hive CLI, synchronizes access control lists when objects are altered via DDL in HiveServer2, and provides consistent authorization between Hive and HDFS resources. The agent has been implemented through custom classes extending Hive authorization hooks. A demo showed the new capabilities working with Ranger, Hive, and Hadoop.
Architecture patterns for distributed, hybrid, edge and global Apache Kafka d...Kai Wähner
Architecture patterns for distributed, hybrid, edge and global Apache Kafka deployments
Multi-cluster and cross-data center deployments of Apache Kafka have become the norm rather than an exception. This session gives an overview of several scenarios that may require multi-cluster solutions and discusses real-world examples with their specific requirements and trade-offs, including disaster recovery, aggregation for analytics, cloud migration, mission-critical stretched deployments and global Kafka.
Key takeaways:
In many scenarios, one Kafka cluster is not enough. Understand different architectures and alternatives for multi-cluster deployments.
Zero data loss and high availability are two key requirements. Understand how to realize this, including trade-offs.
Learn about features and limitations of Kafka for multi cluster deployments
Global Kafka and mission-critical multi-cluster deployments with zero data loss and high availability became the normal, not an exception.
Union membership in the US has declined due to several factors, including companies moving operations overseas and changes in technology eliminating manual labor jobs. The National Labor Relations Act of 1935 established the rights of employees to organize unions and collectively bargain. Employees seek to form unions to gain higher wages, better benefits, job security, and a sense of community. Organizing campaigns involve signing authorization cards and holding representation elections overseen by the NLRB. Collective bargaining between unions and employers covers terms of employment, and can include issues like union security and dues checkoff. Failure to reach agreement can result in strikes, which employers try to prevent through mediation and arbitration.
The slides from the talk I gave in Java.IL's Apr 2019 session.
These slides describe Keycloak, OAuth 2.0, OpenID and SparkBeyond's integration with Keycloak
Oracle Exadata Management with Oracle Enterprise ManagerEnkitec
This document discusses Oracle Exadata management using Oracle Enterprise Manager. It provides an overview of the key capabilities including monitoring of databases, storage cells, and the full Exadata system. It describes how to discover Exadata targets within Enterprise Manager and ensure proper configuration. Troubleshooting tools are also covered to help diagnose any discovery or monitoring issues. The presentation aims to help customers get started with and take full advantage of Exadata management through Enterprise Manager.
Alkin Tezuysal discusses his first 90 days working at ChistaDATA Inc. as EVP of Global Services. He has experience working with databases like MySQL, Oracle, and ClickHouse. ChistaDATA focuses on providing ClickHouse infrastructure operations through managed services, support, and consulting. ClickHouse is an open source columnar database that uses a shared-nothing architecture for high performance analytics workloads.
6 Nines: How Stripe keeps Kafka highly-available across the globe with Donny ...HostedbyConfluent
Availability is a key metric for any Kafka deployment, but when every event is critical the system must be centered around keeping publishers and consumers highly available, even when a Kafka cluster goes down. At Stripe our core business relies on Kafka, and as we outgrew a single Kafka cluster we had to build a multi-cluster system which would fit our needs while supporting a target of 99.9999% availability for our most critical use cases.
In this talk we’ll discuss our solution to this problem: an in-house proxy layer and multi-cluster toplogy which we’ve built and operated over the past 3 years. Our proxy layer enables multiple Kafka clusters to work in coordination across the globe, while hitting our ambitious availability targets and providing clean client abstractions.
In this talk we’ll discuss how our Kafka deployment provides: availability for both publishers and consumers in the face of cluster outages, increased security and observability, simplified cluster maintenance, and global routing for constraints such as data locality. We’ll highlight the benefits & tradeoffs of our approach, the design of our proxy layer, Kafka configuration decisions, and where we’re planning to go from here.
This document provides an introduction to machine learning. It discusses where machine learning is used such as recommending movies or web articles to users. The history and types of machine learning are covered including supervised learning, unsupervised learning, and reinforcement learning. Examples of machine learning algorithms and breakthroughs like Google's AlphaGo and IBM Watson are mentioned. The document concludes by addressing concerns about machine learning and providing references for further learning.
The document discusses HyperLedger Fabric, a permissioned blockchain framework. It provides an overview of key Fabric concepts including its architecture, components, transaction flow, and how it differs from other blockchain platforms like Ethereum. The summary is as follows:
[1] HyperLedger Fabric is a permissioned blockchain framework that uses channels and smart contracts called chaincode to allow for private and confidential transactions between specific network members.
[2] It has a modular architecture consisting of peers that host the ledger and chaincode, an ordering service to sequence transactions into blocks, and a certificate authority for identity management.
[3] Transactions in Fabric are validated by endorsing peers running chaincode, ordered into blocks by
Sharding allows you to distribute load across multiple servers and keep your data balanced across those servers. This session will review MongoDB’s sharding support, including an architectural overview, design principles, and automation.
Introduction to Apache ZooKeeper | Big Data Hadoop Spark Tutorial | CloudxLabCloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2kvXlPd
This CloudxLab Introduction to Apache ZooKeeper tutorial helps you to understand ZooKeeper in detail. Below are the topics covered in this tutorial:
1) Data Model
2) Znode Types
3) Persistent Znode
4) Sequential Znode
5) Architecture
6) Election & Majority Demo
7) Why Do We Need Majority?
8) Guarantees - Sequential consistency, Atomicity, Single system image, Durability, Timeliness
9) ZooKeeper APIs
10) Watches & Triggers
11) ACLs - Access Control Lists
12) Usecases
13) When Not to Use ZooKeeper
Database migration from Sybase ASE to PostgreSQL @2013.pgconf.eualdaschwede80
The talk explains some differences between Sybase ASE and PostgreSQL and shows two different migration strategies - the dump reload process and replication.
The document discusses using blockchain technology to improve healthcare systems. It describes issues with current electronic health records like security risks, data reliability, and high costs. Blockchain could address these issues by creating easy health data exchange, transparent billing, and more secure drug supply chains. The presentation evaluates how blockchain may revolutionize the industry by reducing costs through greater efficiency and optimizing current workflows. It proposes solutions like giving healthcare providers and departments direct access to scheduling and demand data to improve faculty planning and hiring.
Kafka High Availability in multi data center setup with floating Observers wi...HostedbyConfluent
The document discusses how to set up Kafka high availability in a multi-datacenter configuration using floating observers. Observers are regular brokers that are never part of the in-sync replica set for a topic. This allows forced replication to another data center for high availability. The document explains how to create topics that use observers, what happens to existing topics when observers are introduced, and how to distribute load evenly between data centers by preparing observers to float and using rack awareness.
This document discusses using NLP techniques like tokenization, feature extraction, classification, clustering, and anomaly detection to analyze log files. It provides examples of how each technique can be applied including tokenizing log records, extracting features like n-grams and token shapes, classifying records by type or priority level, clustering records to find anomalies, and detecting outliers. The document also recommends tools like NLTK, Scikit-Learn, Logpai and references the author's own work at Insight Engines on log search and analysis products.
In the near future, privacy-preserving authentication methods will flood the market, and they will be based on Zero-Knowledge Proofs. IBM and Microsoft invested in these solutions many years ago.
The slides from the talk I gave in Java.IL's Apr 2019 session.
These slides describe Keycloak, OAuth 2.0, OpenID and SparkBeyond's integration with Keycloak
Oracle Exadata Management with Oracle Enterprise ManagerEnkitec
This document discusses Oracle Exadata management using Oracle Enterprise Manager. It provides an overview of the key capabilities including monitoring of databases, storage cells, and the full Exadata system. It describes how to discover Exadata targets within Enterprise Manager and ensure proper configuration. Troubleshooting tools are also covered to help diagnose any discovery or monitoring issues. The presentation aims to help customers get started with and take full advantage of Exadata management through Enterprise Manager.
Alkin Tezuysal discusses his first 90 days working at ChistaDATA Inc. as EVP of Global Services. He has experience working with databases like MySQL, Oracle, and ClickHouse. ChistaDATA focuses on providing ClickHouse infrastructure operations through managed services, support, and consulting. ClickHouse is an open source columnar database that uses a shared-nothing architecture for high performance analytics workloads.
6 Nines: How Stripe keeps Kafka highly-available across the globe with Donny ...HostedbyConfluent
Availability is a key metric for any Kafka deployment, but when every event is critical the system must be centered around keeping publishers and consumers highly available, even when a Kafka cluster goes down. At Stripe our core business relies on Kafka, and as we outgrew a single Kafka cluster we had to build a multi-cluster system which would fit our needs while supporting a target of 99.9999% availability for our most critical use cases.
In this talk we’ll discuss our solution to this problem: an in-house proxy layer and multi-cluster toplogy which we’ve built and operated over the past 3 years. Our proxy layer enables multiple Kafka clusters to work in coordination across the globe, while hitting our ambitious availability targets and providing clean client abstractions.
In this talk we’ll discuss how our Kafka deployment provides: availability for both publishers and consumers in the face of cluster outages, increased security and observability, simplified cluster maintenance, and global routing for constraints such as data locality. We’ll highlight the benefits & tradeoffs of our approach, the design of our proxy layer, Kafka configuration decisions, and where we’re planning to go from here.
This document provides an introduction to machine learning. It discusses where machine learning is used such as recommending movies or web articles to users. The history and types of machine learning are covered including supervised learning, unsupervised learning, and reinforcement learning. Examples of machine learning algorithms and breakthroughs like Google's AlphaGo and IBM Watson are mentioned. The document concludes by addressing concerns about machine learning and providing references for further learning.
The document discusses HyperLedger Fabric, a permissioned blockchain framework. It provides an overview of key Fabric concepts including its architecture, components, transaction flow, and how it differs from other blockchain platforms like Ethereum. The summary is as follows:
[1] HyperLedger Fabric is a permissioned blockchain framework that uses channels and smart contracts called chaincode to allow for private and confidential transactions between specific network members.
[2] It has a modular architecture consisting of peers that host the ledger and chaincode, an ordering service to sequence transactions into blocks, and a certificate authority for identity management.
[3] Transactions in Fabric are validated by endorsing peers running chaincode, ordered into blocks by
Sharding allows you to distribute load across multiple servers and keep your data balanced across those servers. This session will review MongoDB’s sharding support, including an architectural overview, design principles, and automation.
Introduction to Apache ZooKeeper | Big Data Hadoop Spark Tutorial | CloudxLabCloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2kvXlPd
This CloudxLab Introduction to Apache ZooKeeper tutorial helps you to understand ZooKeeper in detail. Below are the topics covered in this tutorial:
1) Data Model
2) Znode Types
3) Persistent Znode
4) Sequential Znode
5) Architecture
6) Election & Majority Demo
7) Why Do We Need Majority?
8) Guarantees - Sequential consistency, Atomicity, Single system image, Durability, Timeliness
9) ZooKeeper APIs
10) Watches & Triggers
11) ACLs - Access Control Lists
12) Usecases
13) When Not to Use ZooKeeper
Database migration from Sybase ASE to PostgreSQL @2013.pgconf.eualdaschwede80
The talk explains some differences between Sybase ASE and PostgreSQL and shows two different migration strategies - the dump reload process and replication.
The document discusses using blockchain technology to improve healthcare systems. It describes issues with current electronic health records like security risks, data reliability, and high costs. Blockchain could address these issues by creating easy health data exchange, transparent billing, and more secure drug supply chains. The presentation evaluates how blockchain may revolutionize the industry by reducing costs through greater efficiency and optimizing current workflows. It proposes solutions like giving healthcare providers and departments direct access to scheduling and demand data to improve faculty planning and hiring.
Kafka High Availability in multi data center setup with floating Observers wi...HostedbyConfluent
The document discusses how to set up Kafka high availability in a multi-datacenter configuration using floating observers. Observers are regular brokers that are never part of the in-sync replica set for a topic. This allows forced replication to another data center for high availability. The document explains how to create topics that use observers, what happens to existing topics when observers are introduced, and how to distribute load evenly between data centers by preparing observers to float and using rack awareness.
This document discusses using NLP techniques like tokenization, feature extraction, classification, clustering, and anomaly detection to analyze log files. It provides examples of how each technique can be applied including tokenizing log records, extracting features like n-grams and token shapes, classifying records by type or priority level, clustering records to find anomalies, and detecting outliers. The document also recommends tools like NLTK, Scikit-Learn, Logpai and references the author's own work at Insight Engines on log search and analysis products.
In the near future, privacy-preserving authentication methods will flood the market, and they will be based on Zero-Knowledge Proofs. IBM and Microsoft invested in these solutions many years ago.
MongoDB Background and specifics ,
also I provide how to use Mongod Security .
and Basic MongoDB operation by pymongo
我這份文件有介紹MONGODB的特性及限制,Sharding 及 Replicate 的觀悠,Security怎麼作,怎麼用
This document discusses how to connect logs to various network services using Logback. It begins with a brief introduction of common logging frameworks like SLF4J, Log4j 1, Log4j 2 and Logback. It then explains Logback's internal architecture including loggers, appenders and layouts. The main part demonstrates how to develop a custom appender in Logback to send logs to network services by utilizing the ILoggingEvent object. It provides code templates and examples of accessing log content and stack traces. Finally, it introduces some open source Logback appenders and the Logpush service for remote log monitoring.
141. 141
References
1. Distributed locks with Redis
2. The Architecture Twitter Uses To Deal With 150M Active Users,
300K QPS, A 22 MB/S Firehose, And Send Tweets In Under 5 Se
conds
3. BullMQ - Premium Message Queue for NodeJS based on Redis