Newer version is here
https://www.slideshare.net/nowokay/summary-of-jdk10-and-what-will-come-into-jdk11-99363835
Summary of JDK10
and What will come into JDK11 so far
Newer version about JDK10 and 11 is here
https://www.slideshare.net/nowokay/summary-of-jdk10-and-what-will-come-into-jdk11-99363835
The material for the presentation of the JJUG CCC 2018 Spring
Lucene 4.0 is on its way to deliver a tremendous amount of new features and improvements. Beside Real-Time Search & Flexible Indexing DocValues aka. Column Stride Fields is one of the "next generation" features
DocValues aka. Column Stride Fields in Lucene 4.0 - By Willnauer Simonlucenerevolution
See conference video - http://www.lucidimagination.com/devzone/events/conferences/revolution/2011
Lucene 4.0 is on its way to deliver a tremendous amount of new features and improvements. Beside
Real-Time Search & Flexible Indexing DocValues aka. Column Stride Fields is one of the “next
generation” features. DocValues enable Lucene to efficiently store and retrieve type-safe Document
& Value pairs in a column stride fashion either entirely memory resident random access or disk
resident iterator based without the need to un-invert fields. Its final goal is to provide a
independently update-able per document storage for scoring, sorting or even filtering. This talk will
introduce the current state of development, implementation details, its features and how DocValues
have been integrated into Lucene’s Codec API for full extendability.
This document provides an overview and summary of the Java Content Repository (JCR) specification and Apache Jackrabbit implementation. It discusses how JCR combines advantages of file systems and databases by allowing structured and unstructured content to be stored together in a single repository. It also summarizes how to connect to a repository, interact with nodes and properties, perform searches and queries, and leverage advanced features like observation and versioning. The document promotes JCR as a standard Java API and Apache Jackrabbit as a widely used open source implementation.
Apache Jackrabbit Oak is a new JCR implementation with a completely new architecture. Based on concepts like eventual consistency and multi-version concurrency control, and borrowing ideas from distributed version control systems and cloud-scale databases, the Oak architecture is a major leap ahead for Jackrabbit. This presentation describes the Oak architecture and shows what it means for the scalability and performance of modern content applications. Changes to existing Jackrabbit functionality are described and the migration process is explained.
JRuby allows developers to write plugins for data processing systems like Norikra and Embulk in Ruby while taking advantage of Java libraries and the JVM. Norikra is a stream processing system that allows SQL queries over data streams. It is written in JRuby and uses the Java Esper library. Embulk is an open-source ETL tool that loads data between databases and file formats using plugins. Both systems use a plugin architecture where plugins can be written in JRuby or Java and are distributed as Ruby gems. This allows for a pluggable ecosystem that benefits from Ruby's productivity while utilizing Java libraries and the JVM's performance.
Spark real world use cases and optimizationsGal Marder
This document provides an overview of Spark, its core abstraction of resilient distributed datasets (RDDs), and common transformations and actions. It discusses how Spark partitions and distributes data across a cluster, its lazy evaluation model, and the concept of dependencies between RDDs. Common use cases like word counting, bucketing user data, finding top results, and analytics reporting are demonstrated. Key topics covered include avoiding expensive shuffle operations, choosing optimal aggregation methods, and potentially caching data in memory.
"In this session, Twitter engineer Alex Payne will explore how the popular social messaging service builds scalable, distributed systems in the Scala programming language. Since 2008, Twitter has moved the development of its most critical systems to Scala, which blends object-oriented and functional programming with the power, robust tooling, and vast library support of the Java Virtual Machine. Find out how to use the Scala components that Twitter has open sourced, and learn the patterns they employ for developing core infrastructure components in this exciting and increasingly popular language."
OSMC 2016 - Monitor your infrastructure with Elastic Beats by Monica SarbuNETWAYS
Monica ist Mit-Schöpferin von Elastic Beats. Bevor sie Beats erfand, arbeitete sie als Core Developer für IPTEGO, einem Start-Up Unternehmen aus Berlin, das eine komplette Monitoring und Trouble-Shooting Solution für VoIP Netzwerke anbietet. Das Produkt wurde weltweit verkauft, und wird derzeit von großen Firmen der Telekommunikationsbranche verwendet.
Tuning Solr and its Pipeline for Logs: Presented by Rafał Kuć & Radu Gheorghe...Lucidworks
The document summarizes key points from a presentation on optimizing Solr and log pipelines for time-series data. The presentation covered using time-based Solr collections that rotate based on size, tiering hot and cold clusters, tuning OS and Solr settings, parsing logs, buffering pipelines, and shipping logs using protocols like UDP, TCP, and Kafka. The overall conclusions were that tuning segments per tier and max merged segment size improved indexing throughput, and that simple, reliable pipelines like Filebeat to Kafka or rsyslog over UNIX sockets generally work best.
LevelDB is an embedded key-value store developed by Google that is optimized for fast read and write operations. It can be used as an embedded database or with networking protocols. LevelDB stores data on disk and supports keys and values in arbitrary byte arrays. The LevelUp Node.js wrapper provides an interface to perform common operations like put, get, delete, batch operations, and iterating over data streams. LevelDB can store JSON objects by setting the valueEncoding option to 'json'.
In the big data world, our data stores communicate over an asynchronous, unreliable network to provide a facade of consistency. However, to really understand the guarantees of these systems, we must understand the realities of networks and test our data stores against them.
Jepsen is a tool which simulates network partitions in data stores and helps us understand the guarantees of our systems and its failure modes. In this talk, I will help you understand why you should care about network partitions and how can we test datastores against partitions using Jepsen. I will explain what Jepsen is and how it works and the kind of tests it lets you create. We will try to understand the subtleties of distributed consensus, the CAP theorem and demonstrate how different data stores such as MongoDB, Cassandra, Elastic and Solr behave under network partitions. Finally, I will describe the results of the tests I wrote using Jepsen for Apache Solr and discuss the kinds of rare failures which were found by this excellent tool.
Wed, August 24, 9:00am – 9:45am
Youtube: https://youtu.be/mCdoq7P5Zkw
First Name: Norm
Last Name: Green
Email where you can always be reached: [email protected]
Type: Talk
Abstract: GemStone/64 product update and road map. A review of what's
new in version 3.3 and a preview to what we're working on for version
3.4. This year, I will also start with a few slides describing what
GemStone is and benefits of using it ("GemStone-101").
Bio: Norm Green started his career in 1989 at IBM in Toronto, Canada
as a quality assurance engineer. In 1993, he moved to the DACS (Data
Acquisition and Control System) team where he helped design and build
site-wide data collection system in VisualWorks and GemStone/S
Smallalk.
In 1996, he joined GemStone Systems as a Senior Consultant and
traveled the world helping GemStone/S customers be successful.
Currently, Norm lives near Portland, Oregon and holds the position of
Chief Technical Officer at GemTalk Systems.
Presentation by Tomaz Cerar (Red Hat), delivered at the London JBoss User Group event on the 12th of February 2014.
Watch the video here: http://www.youtube.com/watch?v=eu9K5NLUKBI
Join London JBUG: http://www.c2b2.co.uk/jbug
This document provides information about integrating Apache Solr and Apache Spark. It discusses using Solr as a data source and sink for Spark applications, including indexing data from Spark jobs into Solr in real-time and exposing Solr query results as Spark RDDs. The document also summarizes the Spark Streaming and RDD APIs and provides code examples for indexing tweets from Spark Streaming into Solr and reading from Solr into a DataFrame.
NYJavaSIG - Big Data Microservices w/ SpeedmentSpeedment, Inc.
Microservices solutions can provide fast access to large datasets by synchronizing SQL data into an in-JVM memory store and using key-value and column key stores. This allows querying terabytes of data in microseconds by mapping the data in memory and providing application programming interfaces. The solution uses periodic synchronization to initially load and periodically reload data, as well as reactive synchronization to capture and replay database changes.
How to JavaOne 2016 - Generate Customized Java 8 Code from Your Database [TUT...Malin Weiss
The best code is the one you never need to write. Using code generation and automated builds, you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it are handed over to a machine? In this tutorial, you will learn how to use open source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you, as a developer, 100 percent control of the generated code. This will not only increase your productivity but also help you build safer, more maintainable Java applications and is a perfect solution for Microservices.
This document provides an overview of key concepts in the Java Virtual Machine (JVM) including memory management, garbage collection techniques, class loading, execution engines, multi-threading, and the Java Native Interface (JNI). It discusses topics such as heap vs non-heap memory, minor vs major garbage collection, just-in-time compilation, safe points, and how to call native methods from Java using JNI.
Spark provides tools for distributed processing of large datasets across clusters. It includes APIs for distributed datasets called RDDs (Resilient Distributed Datasets) and transformations and actions that can be performed on those datasets in parallel. Key features of Spark include the Spark Shell for interactive use, DataFrames for structured data processing, and Spark Streaming for real-time data analysis.
Docker is an open-source project to easily create lightweight, portable, self-sufficient containers from any application. The same container that a developer builds and tests on a laptop can run at scale, in production, on VMs, bare metal, OpenStack clusters, public clouds and more.
Concurrency and Multithreading Demistified - Reversim Summit 2014Haim Yadid
Life as a software engineer is so exciting! Computing power continue to rise exponentially, software demands continue to rise exponentially as well, so far so good. The bad news are that in the last decade the computing power of single threaded application remains almost flat.
If you decide to continue ignoring concurrency and multi-threading the gap between the problems you are able to solve and your hardware capabilities will continue to rise. In this session we will discuss different approaches for taming the concurrency beast, such as shared mutability,shared immutability and isolated mutability actors, STM, etc we will discuss the shortcomings and the dangers of each approach and we will compare different programming languages and how they choose to tackle/ignore concurrency.
Scala io2013 : Our journey from UML/MDD to Scala macrosebiznext
This document discusses moving from UML modeling to using Scala macros to define a domain-specific language (DSL) for modeling database entities and queries. It describes issues with UML like lack of efficiency and impedance mismatch. Scala macros allow defining a DSL that is compiled into type-checked code and avoids runtime overhead. An example DSL defines entities, relationships, constraints and generates corresponding Slick code. The implementation uses both dynamic and macro features to allow type-checked queries defined at the call site. The DSL approach reduced code and improved delivery time over the UML-based workflow.
Bringing Concurrency to Ruby - RubyConf India 2014Charles Nutter
The document discusses bringing concurrency to Ruby. It begins by defining concurrency and parallelism, noting that both are needed but platforms only enable parallelism if jobs can split into concurrent tasks. It reviews concurrency and parallelism in popular Ruby platforms like MRI, JRuby, and Rubinius. The document outlines four rules for concurrency and discusses techniques like immutable data, locking, atomics, and specialized collections for mutable data. It highlights libraries that provide high-level concurrency abstractions like Celluloid for actors and Sidekiq for background jobs.
Experiences with Evangelizing Java Within the DatabaseMarcelo Ochoa
The document discusses experiences with evangelizing the use of Java within Oracle databases. It provides a timeline of Java support in Oracle databases from 8i to 12c. It describes developing, testing, and deploying database-resident Java applications. Examples discussed include a content management system and RESTful web services implemented as stored procedures, as well as the Scotas OLS product for embedded Solr search. The conclusion covers challenges with open source projects, impedance mismatch between databases and Java, and lack of overlap between skillsets.
This is a talk I did for JavaOne 2009. The focus of the talk was memory management and system monitoring with freely available tools that are in the jdk or open source.
Summary of JDK10 and What will come into JDK11なおき きしだ
The document summarizes JDK 10, what is coming in JDK 11, and Java support options. Key points include Java moving to a 6-month release cycle with 3-year Long Term Support releases, features in JDK 10 like local variable type inference and JDK 11 features like switch expressions. It also discusses changes to support like Oracle JDK only for customers, OpenJDK and AdoptOpenJDK providing Long Term Support, and commercial support from Zulu.
New thing in JDK10 even that scala-er should knowなおき きしだ
JDK 10 will be released on March 20, 2018 with 12 new features. Key changes include a new 6-month release cycle, modularization of the garbage collector, experimental Java-based JIT compiler, local variable type inference, parallel full GC for G1, application class-data sharing between JVMs, ability to stop individual threads, and support for alternative memory devices like non-volatile RAM. JDK 10 also enhances support for Docker and Unicode extensions.
OSMC 2016 - Monitor your infrastructure with Elastic Beats by Monica SarbuNETWAYS
Monica ist Mit-Schöpferin von Elastic Beats. Bevor sie Beats erfand, arbeitete sie als Core Developer für IPTEGO, einem Start-Up Unternehmen aus Berlin, das eine komplette Monitoring und Trouble-Shooting Solution für VoIP Netzwerke anbietet. Das Produkt wurde weltweit verkauft, und wird derzeit von großen Firmen der Telekommunikationsbranche verwendet.
Tuning Solr and its Pipeline for Logs: Presented by Rafał Kuć & Radu Gheorghe...Lucidworks
The document summarizes key points from a presentation on optimizing Solr and log pipelines for time-series data. The presentation covered using time-based Solr collections that rotate based on size, tiering hot and cold clusters, tuning OS and Solr settings, parsing logs, buffering pipelines, and shipping logs using protocols like UDP, TCP, and Kafka. The overall conclusions were that tuning segments per tier and max merged segment size improved indexing throughput, and that simple, reliable pipelines like Filebeat to Kafka or rsyslog over UNIX sockets generally work best.
LevelDB is an embedded key-value store developed by Google that is optimized for fast read and write operations. It can be used as an embedded database or with networking protocols. LevelDB stores data on disk and supports keys and values in arbitrary byte arrays. The LevelUp Node.js wrapper provides an interface to perform common operations like put, get, delete, batch operations, and iterating over data streams. LevelDB can store JSON objects by setting the valueEncoding option to 'json'.
In the big data world, our data stores communicate over an asynchronous, unreliable network to provide a facade of consistency. However, to really understand the guarantees of these systems, we must understand the realities of networks and test our data stores against them.
Jepsen is a tool which simulates network partitions in data stores and helps us understand the guarantees of our systems and its failure modes. In this talk, I will help you understand why you should care about network partitions and how can we test datastores against partitions using Jepsen. I will explain what Jepsen is and how it works and the kind of tests it lets you create. We will try to understand the subtleties of distributed consensus, the CAP theorem and demonstrate how different data stores such as MongoDB, Cassandra, Elastic and Solr behave under network partitions. Finally, I will describe the results of the tests I wrote using Jepsen for Apache Solr and discuss the kinds of rare failures which were found by this excellent tool.
Wed, August 24, 9:00am – 9:45am
Youtube: https://youtu.be/mCdoq7P5Zkw
First Name: Norm
Last Name: Green
Email where you can always be reached: [email protected]
Type: Talk
Abstract: GemStone/64 product update and road map. A review of what's
new in version 3.3 and a preview to what we're working on for version
3.4. This year, I will also start with a few slides describing what
GemStone is and benefits of using it ("GemStone-101").
Bio: Norm Green started his career in 1989 at IBM in Toronto, Canada
as a quality assurance engineer. In 1993, he moved to the DACS (Data
Acquisition and Control System) team where he helped design and build
site-wide data collection system in VisualWorks and GemStone/S
Smallalk.
In 1996, he joined GemStone Systems as a Senior Consultant and
traveled the world helping GemStone/S customers be successful.
Currently, Norm lives near Portland, Oregon and holds the position of
Chief Technical Officer at GemTalk Systems.
Presentation by Tomaz Cerar (Red Hat), delivered at the London JBoss User Group event on the 12th of February 2014.
Watch the video here: http://www.youtube.com/watch?v=eu9K5NLUKBI
Join London JBUG: http://www.c2b2.co.uk/jbug
This document provides information about integrating Apache Solr and Apache Spark. It discusses using Solr as a data source and sink for Spark applications, including indexing data from Spark jobs into Solr in real-time and exposing Solr query results as Spark RDDs. The document also summarizes the Spark Streaming and RDD APIs and provides code examples for indexing tweets from Spark Streaming into Solr and reading from Solr into a DataFrame.
NYJavaSIG - Big Data Microservices w/ SpeedmentSpeedment, Inc.
Microservices solutions can provide fast access to large datasets by synchronizing SQL data into an in-JVM memory store and using key-value and column key stores. This allows querying terabytes of data in microseconds by mapping the data in memory and providing application programming interfaces. The solution uses periodic synchronization to initially load and periodically reload data, as well as reactive synchronization to capture and replay database changes.
How to JavaOne 2016 - Generate Customized Java 8 Code from Your Database [TUT...Malin Weiss
The best code is the one you never need to write. Using code generation and automated builds, you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it are handed over to a machine? In this tutorial, you will learn how to use open source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you, as a developer, 100 percent control of the generated code. This will not only increase your productivity but also help you build safer, more maintainable Java applications and is a perfect solution for Microservices.
This document provides an overview of key concepts in the Java Virtual Machine (JVM) including memory management, garbage collection techniques, class loading, execution engines, multi-threading, and the Java Native Interface (JNI). It discusses topics such as heap vs non-heap memory, minor vs major garbage collection, just-in-time compilation, safe points, and how to call native methods from Java using JNI.
Spark provides tools for distributed processing of large datasets across clusters. It includes APIs for distributed datasets called RDDs (Resilient Distributed Datasets) and transformations and actions that can be performed on those datasets in parallel. Key features of Spark include the Spark Shell for interactive use, DataFrames for structured data processing, and Spark Streaming for real-time data analysis.
Docker is an open-source project to easily create lightweight, portable, self-sufficient containers from any application. The same container that a developer builds and tests on a laptop can run at scale, in production, on VMs, bare metal, OpenStack clusters, public clouds and more.
Concurrency and Multithreading Demistified - Reversim Summit 2014Haim Yadid
Life as a software engineer is so exciting! Computing power continue to rise exponentially, software demands continue to rise exponentially as well, so far so good. The bad news are that in the last decade the computing power of single threaded application remains almost flat.
If you decide to continue ignoring concurrency and multi-threading the gap between the problems you are able to solve and your hardware capabilities will continue to rise. In this session we will discuss different approaches for taming the concurrency beast, such as shared mutability,shared immutability and isolated mutability actors, STM, etc we will discuss the shortcomings and the dangers of each approach and we will compare different programming languages and how they choose to tackle/ignore concurrency.
Scala io2013 : Our journey from UML/MDD to Scala macrosebiznext
This document discusses moving from UML modeling to using Scala macros to define a domain-specific language (DSL) for modeling database entities and queries. It describes issues with UML like lack of efficiency and impedance mismatch. Scala macros allow defining a DSL that is compiled into type-checked code and avoids runtime overhead. An example DSL defines entities, relationships, constraints and generates corresponding Slick code. The implementation uses both dynamic and macro features to allow type-checked queries defined at the call site. The DSL approach reduced code and improved delivery time over the UML-based workflow.
Bringing Concurrency to Ruby - RubyConf India 2014Charles Nutter
The document discusses bringing concurrency to Ruby. It begins by defining concurrency and parallelism, noting that both are needed but platforms only enable parallelism if jobs can split into concurrent tasks. It reviews concurrency and parallelism in popular Ruby platforms like MRI, JRuby, and Rubinius. The document outlines four rules for concurrency and discusses techniques like immutable data, locking, atomics, and specialized collections for mutable data. It highlights libraries that provide high-level concurrency abstractions like Celluloid for actors and Sidekiq for background jobs.
Experiences with Evangelizing Java Within the DatabaseMarcelo Ochoa
The document discusses experiences with evangelizing the use of Java within Oracle databases. It provides a timeline of Java support in Oracle databases from 8i to 12c. It describes developing, testing, and deploying database-resident Java applications. Examples discussed include a content management system and RESTful web services implemented as stored procedures, as well as the Scotas OLS product for embedded Solr search. The conclusion covers challenges with open source projects, impedance mismatch between databases and Java, and lack of overlap between skillsets.
This is a talk I did for JavaOne 2009. The focus of the talk was memory management and system monitoring with freely available tools that are in the jdk or open source.
Summary of JDK10 and What will come into JDK11なおき きしだ
The document summarizes JDK 10, what is coming in JDK 11, and Java support options. Key points include Java moving to a 6-month release cycle with 3-year Long Term Support releases, features in JDK 10 like local variable type inference and JDK 11 features like switch expressions. It also discusses changes to support like Oracle JDK only for customers, OpenJDK and AdoptOpenJDK providing Long Term Support, and commercial support from Zulu.
New thing in JDK10 even that scala-er should knowなおき きしだ
JDK 10 will be released on March 20, 2018 with 12 new features. Key changes include a new 6-month release cycle, modularization of the garbage collector, experimental Java-based JIT compiler, local variable type inference, parallel full GC for G1, application class-data sharing between JVMs, ability to stop individual threads, and support for alternative memory devices like non-volatile RAM. JDK 10 also enhances support for Docker and Unicode extensions.
Java 9 is just around the corner. In this session, we'll describe the new modularization support (Jigsaw), new JDK tools, enhanced APIs and many performance improvements that were added to the new version.
In the modern "World of Java" there was a lot of interesting things going on in the last year, and many things are yet to come. A bit more than a year ago we got a long-awaited Java 9 with Jigsaw modularization and many other new features. In October we "moved Java forward faster" and switched to Java 11, with even more new features, following a new release model and versioning scheme.
Real time Analytics with Apache Kafka and Apache SparkRahul Jain
A presentation cum workshop on Real time Analytics with Apache Kafka and Apache Spark. Apache Kafka is a distributed publish-subscribe messaging while other side Spark Streaming brings Spark's language-integrated API to stream processing, allows to write streaming applications very quickly and easily. It supports both Java and Scala. In this workshop we are going to explore Apache Kafka, Zookeeper and Spark with a Web click streaming example using Spark Streaming. A clickstream is the recording of the parts of the screen a computer user clicks on while web browsing.
The document provides an overview of the Java platform, including its evolution, structure, and key components. It discusses how Java programs are compiled and run on the Java Virtual Machine (JVM). It also compares Java to C++ and provides examples of coding Java programs using IDEs like NetBeans and Eclipse. The document covers many aspects of Java in detail across several sections.
Scala is widely used at Treasure Data for data analytics workflows, management of the Presto query engine, and open-source libraries. Some key uses of Scala include analyzing query logs to optimize Presto performance, developing Prestobase using Scala macros and libraries like Airframe, and integrating Spark with Treasure Data. Treasure Data engineers have also created several open-source Scala libraries, such as wvlet-log for logging and Airframe for dependency injection, and sbt plugins to facilitate packaging, testing, and deployment.
Java 9 introduced modules that provide strong encapsulation and reliable configuration. It also included new APIs like ProcessHandle and private methods in interfaces. Java 10 added local variable type inference with the var keyword and improved support for containerized environments. Java 11 continues enhancements with lambda parameters declared using var and an experimental garbage collector. All future releases will occur every six months with long term support versions every three years.
The document summarizes the evolution of Java from versions 8 to the upcoming version 19. It outlines the major new features introduced in each version, including module system in Java 9, local variable type inference in Java 10, and records in Java 16. It also discusses some ongoing projects that aim to further enhance Java, such as Project Loom, Project Panama, Project Valhalla and Project Amber. Key language concepts like encapsulation, private methods in interfaces, pattern matching and sealed classes are briefly explained.
Blocks is a cool concept and is very much needed for performance improvements and responsiveness. GCD helps run blocks effortlessly by scheduling on a desired queue, priority and lots more.
The venerable Servlet Container still has some performance tricks up its sleeve - this talk will demonstrate Apache Tomcat's stability under high load, describe some do's (and some don'ts!), explain how to performance test a Servlet-based application, troubleshoot and tune the container and your application and compare the performance characteristics of the different Tomcat connectors. The presenters will share their combined experience supporting real Tomcat applications for over 20 years and show how a few small changes can make a big, big difference.
This document provides an introduction to the Java programming language. It discusses Java's unique features such as safety, web capabilities, and standard libraries. It also covers Java versions and their enhancements over time. The document demonstrates how to install Java, write a basic "Hello World" application and applet, handle command line arguments, and customize applets using parameters. It summarizes that Java supports both standalone applications and web development across platforms through its use of bytecode run on the Java Virtual Machine.
The document discusses strategies for scaling massive Elasticsearch clusters to handle large volumes of data and queries. It covers techniques such as controlling shard and replica placement, indexing thousands of documents per second, querying data in tens of milliseconds, handling multilingual content, and monitoring cluster performance. The key approaches include configuring indices, shards, and replicas; routing documents and queries for optimal distribution; tuning refresh intervals and merge factors; and using tools to monitor nodes, queries, caching, and garbage collection.
Grand Central Dispatch (GCD) was created by Apple to make it easier to write concurrent code for multi-core systems. It shifts thread and task management from apps to the operating system. Units of work are described as blocks of code, while queues organize blocks based on execution needs. GCD has a multi-core engine that assigns blocks from app queues to OS-managed threads, removing the need for apps to directly use threads. Blocks are lightweight anonymous functions that can capture state and be passed between queues and threads for asynchronous execution. Common queues include the main queue for UI updates and global queues for general-purpose work.
Apache Geode is an open source in-memory data grid that provides data distribution, replication and high availability. It can be used for caching, messaging and interactive queries. The presentation discusses Geode concepts like cache, region and member. It provides examples of how large companies use Geode for applications requiring real-time response, high concurrency and global data visibility. Geode's performance comes from minimizing data copying and contention through flexible consistency and partitioning. The project is now hosted by Apache and the community is encouraged to get involved through mailing lists, code contributions and example applications.
Java is a programming language invented by James Gosling and others in 1994.
originally named Oak ,was developed as a part of the Green project at the Sun Company.
Java 7 is latest stable release
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...confluent
RocksDB is the default state store for Kafka Streams. In this talk, we will discuss how to improve single node performance of the state store by tuning RocksDB and how to efficiently identify issues in the setup. We start with a short description of the RocksDB architecture. We discuss how Kafka Streams restores the state stores from Kafka by leveraging RocksDB features for bulk loading of data. We give examples of hand-tuning the RocksDB state stores based on Kafka Streams metrics and RocksDB’s metrics. At the end, we dive into a few RocksDB command line utilities that allow you to debug your setup and dump data from a state store. We illustrate the usage of the utilities with a few real-life use cases. The key takeaway from the session is the ability to understand the internal details of the default state store in Kafka Streams so that engineers can fine-tune their performance for different varieties of workloads and operate the state stores in a more robust manner.
This document summarizes a presentation about Oracle's GraalVM and how it can be used to run PHP code. It discusses GraalVM's just-in-time compilation capabilities and how Truffle allows PHP to run on GraalVM. Benchmark results show that a Truffle-based PHP on GraalVM has significantly faster performance than PHP's default interpreter or just-in-time compiler.
これからのコンピューティングの変化とこれからのプログラミング in 福岡 2018/12/8なおき きしだ
Moore's law describes the long-term trend that the number of transistors on integrated circuits doubles approximately every two years. This trend has continued for more than half a century and is a consequence of technological improvements that shrink the scale of components and allow for greater integration of more transistors on a single microchip over time. However, continued progress is not guaranteed and physical and technical limits may cause this trend to end.
This document contains instructions for accessing various online resources related to computational fluid dynamics (CFD). It lists specific web addresses for CFD tutorial pages, reference manuals, and conference proceedings. It also provides contact information for a CFD support team.
- Oracle announced in 2017 that Java would be released every 6 months, with feature releases in March and September and maintenance releases every 3 months in between.
- Support is provided until the next feature release, with Long Term Support provided every 3 years for the Oracle JDK.
- The new release cycle was criticized for being too short, as tools and testing need more than 6 months.
- The version numbering was changed, with JDK 10 being the next feature release in 2018.
Adobe Lightroom Classic Crack FREE Latest link 2025kashifyounis067
🌍📱👉COPY LINK & PASTE ON GOOGLE http://drfiles.net/ 👈🌍
Adobe Lightroom Classic is a desktop-based software application for editing and managing digital photos. It focuses on providing users with a powerful and comprehensive set of tools for organizing, editing, and processing their images on their computer. Unlike the newer Lightroom, which is cloud-based, Lightroom Classic stores photos locally on your computer and offers a more traditional workflow for professional photographers.
Here's a more detailed breakdown:
Key Features and Functions:
Organization:
Lightroom Classic provides robust tools for organizing your photos, including creating collections, using keywords, flags, and color labels.
Editing:
It offers a wide range of editing tools for making adjustments to color, tone, and more.
Processing:
Lightroom Classic can process RAW files, allowing for significant adjustments and fine-tuning of images.
Desktop-Focused:
The application is designed to be used on a computer, with the original photos stored locally on the hard drive.
Non-Destructive Editing:
Edits are applied to the original photos in a non-destructive way, meaning the original files remain untouched.
Key Differences from Lightroom (Cloud-Based):
Storage Location:
Lightroom Classic stores photos locally on your computer, while Lightroom stores them in the cloud.
Workflow:
Lightroom Classic is designed for a desktop workflow, while Lightroom is designed for a cloud-based workflow.
Connectivity:
Lightroom Classic can be used offline, while Lightroom requires an internet connection to sync and access photos.
Organization:
Lightroom Classic offers more advanced organization features like Collections and Keywords.
Who is it for?
Professional Photographers:
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Those with extensive photo collections may prefer Lightroom Classic's local storage and robust organization features.
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Users who prefer a more traditional desktop workflow, with their original photos stored on their computer, will find Lightroom Classic a good fit.
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Adobe Illustrator is a powerful, professional-grade vector graphics software used for creating a wide range of designs, including logos, icons, illustrations, and more. Unlike raster graphics (like photos), which are made of pixels, vector graphics in Illustrator are defined by mathematical equations, allowing them to be scaled up or down infinitely without losing quality.
Here's a more detailed explanation:
Key Features and Capabilities:
Vector-Based Design:
Illustrator's foundation is its use of vector graphics, meaning designs are created using paths, lines, shapes, and curves defined mathematically.
Scalability:
This vector-based approach allows for designs to be resized without any loss of resolution or quality, making it suitable for various print and digital applications.
Design Creation:
Illustrator is used for a wide variety of design purposes, including:
Logos and Brand Identity: Creating logos, icons, and other brand assets.
Illustrations: Designing detailed illustrations for books, magazines, web pages, and more.
Marketing Materials: Creating posters, flyers, banners, and other marketing visuals.
Web Design: Designing web graphics, including icons, buttons, and layouts.
Text Handling:
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Brushes and Effects:
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Integration with Other Adobe Software:
Illustrator integrates seamlessly with other Adobe Creative Cloud apps like Photoshop, InDesign, and Dreamweaver, facilitating a smooth workflow.
Why Use Illustrator?
Professional-Grade Features:
Illustrator offers a comprehensive set of tools and features for professional design work.
Versatility:
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Industry Standard:
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Creative Freedom:
It empowers designers to create detailed, high-quality graphics with a high degree of control and precision.
This presentation explores code comprehension challenges in scientific programming based on a survey of 57 research scientists. It reveals that 57.9% of scientists have no formal training in writing readable code. Key findings highlight a "documentation paradox" where documentation is both the most common readability practice and the biggest challenge scientists face. The study identifies critical issues with naming conventions and code organization, noting that 100% of scientists agree readable code is essential for reproducible research. The research concludes with four key recommendations: expanding programming education for scientists, conducting targeted research on scientific code quality, developing specialized tools, and establishing clearer documentation guidelines for scientific software.
Presented at: The 33rd International Conference on Program Comprehension (ICPC '25)
Date of Conference: April 2025
Conference Location: Ottawa, Ontario, Canada
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Mastering Fluent Bit: Ultimate Guide to Integrating Telemetry Pipelines with ...Eric D. Schabell
It's time you stopped letting your telemetry data pressure your budgets and get in the way of solving issues with agility! No more I say! Take back control of your telemetry data as we guide you through the open source project Fluent Bit. Learn how to manage your telemetry data from source to destination using the pipeline phases covering collection, parsing, aggregation, transformation, and forwarding from any source to any destination. Buckle up for a fun ride as you learn by exploring how telemetry pipelines work, how to set up your first pipeline, and exploring several common use cases that Fluent Bit helps solve. All this backed by a self-paced, hands-on workshop that attendees can pursue at home after this session (https://o11y-workshops.gitlab.io/workshop-fluentbit).
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Pixologic ZBrush, now developed by Maxon, is a premier digital sculpting and painting software renowned for its ability to create highly detailed 3D models. Utilizing a unique "pixol" technology, ZBrush stores depth, lighting, and material information for each point on the screen, allowing artists to sculpt and paint with remarkable precision .
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The two main methods for installing standalone licenses of SOLIDWORKS are clean installation and parallel installation (the process is different ...
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PDF Reader Pro is a software application, often referred to as an AI-powered PDF editor and converter, designed for viewing, editing, annotating, and managing PDF files. It supports various PDF functionalities like merging, splitting, converting, and protecting PDFs. Additionally, it can handle tasks such as creating fillable forms, adding digital signatures, and performing optical character recognition (OCR).
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Join Ajay Sarpal and Miray Vu to learn about key Marketo Engage enhancements. Discover improved in-app Salesforce CRM connector statistics for easy monitoring of sync health and throughput. Explore new Salesforce CRM Synch Dashboards providing up-to-date insights into weekly activity usage, thresholds, and limits with drill-down capabilities. Learn about proactive notifications for both Salesforce CRM sync and product usage overages. Get an update on improved Salesforce CRM synch scale and reliability coming in Q2 2025.
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Microsoft AI Nonprofit Use Cases and Live Demo_2025.04.30.pdfTechSoup
In this webinar we will dive into the essentials of generative AI, address key AI concerns, and demonstrate how nonprofits can benefit from using Microsoft’s AI assistant, Copilot, to achieve their goals.
This event series to help nonprofits obtain Copilot skills is made possible by generous support from Microsoft.
What You’ll Learn in Part 2:
Explore real-world nonprofit use cases and success stories.
Participate in live demonstrations and a hands-on activity to see how you can use Microsoft 365 Copilot in your own work!
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Adobe After Effects is a software application used for creating motion graphics, special effects, and video compositing. It's widely used in TV and film post-production, as well as for creating visuals for online content, presentations, and more. While it can be used to create basic animations and designs, its primary strength lies in adding visual effects and motion to videos and graphics after they have been edited.
Here's a more detailed breakdown:
Motion Graphics:
.
After Effects is powerful for creating animated titles, transitions, and other visual elements to enhance the look of videos and presentations.
Visual Effects:
.
It's used extensively in film and television for creating special effects like green screen compositing, object manipulation, and other visual enhancements.
Video Compositing:
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After Effects allows users to combine multiple video clips, images, and graphics to create a final, cohesive visual.
Animation:
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It uses keyframes to create smooth, animated sequences, allowing for precise control over the movement and appearance of objects.
Integration with Adobe Creative Cloud:
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After Effects is part of the Adobe Creative Cloud, a suite of software that includes other popular applications like Photoshop and Premiere Pro.
Post-Production Tool:
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After Effects is primarily used in the post-production phase, meaning it's used to enhance the visuals after the initial editing of footage has been completed.
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Hironori Washizaki, "Landscape of Requirements Engineering for/by AI through Literature Review," RAISE 2025: Workshop on Requirements engineering for AI-powered SoftwarE, 2025.
Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora
Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.
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Maxon Cinema 4D 2025 is the latest version of the Maxon's 3D software, released in September 2024, and it builds upon previous versions with new tools for procedural modeling and animation, as well as enhancements to particle, Pyro, and rigid body simulations. CG Channel also mentions that Cinema 4D 2025.2, released in April 2025, focuses on spline tools and unified simulation enhancements.
Key improvements and features of Cinema 4D 2025 include:
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Spline Tools: Enhanced spline tools for motion graphics and animation, including spline modifiers from Rocket Lasso now included for all subscribers.
Unified Simulation & Particles: Refined physics-based effects and improved particle systems.
Boolean System: Modernized boolean system for precise 3D modeling.
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In essence, Cinema 4D 2025 is a major update that provides artists with more powerful tools and workflows for creating 3D content, particularly in the fields of motion graphics, VFX, and visualization.
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora
Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.
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Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval.
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Who Watches the Watchmen (SciFiDevCon 2025)Allon Mureinik
Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe.
We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved?
Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security.
Talk from SciFiDevCon 2025
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6. Java new release cycle.
• Feature release every 6 months
– March and September(春分の⽇/秋分の⽇)
• Maintenance release every 3 months
– April and July for March release
– October and January for September release
• Long Term Support every 3 years
– The first LTS is for JDK 11
• Oracle JDK will be for only Oracle
customer
– Use OpenJDK instead.
8. Java SE 8 support is extended
• Oracle has extended Java SE 8
support at least until 2019/1
• It is available for the personal use
until 2020/12
• Java SE 8 support will finish after 3
months of JDK 11 release.
• We should move to JDK 11 by 2019/1
http://www.oracle.com/technetwork/jp/java/eol-135779-ja.html
9. Desktop technology
• Applet and Web Start is no longer
supported after JDK 11
• JavaFX will not be bundled with JDK11
– So far OpenJDK had not bundled JavaFX
• AWT and Swing will be supported
– There are many commits for JDK 11
11. Java 10 JEPs
• 286 Local-Variable Type Inference
• 296 Consolidate the Repository
• 304 GC Interface
• 307 Parallel Full GC for G1
• 310 Application Class-Data Sharing
• 312 Thread-Local Handshakes
• 313 Remove the Native-Header Generation Tool(javah)
• 314 Additional Unicode Language-Tag Extensions
• 316 Heap Allocation on Alternative Momory Devices
• 317 Experimental Java-Based JIT Compiler
• 319 Root Certificates
• 322 Time-Based Release Versioning
12. 286: Local-Variable Type
Inferences
• var list = new ArrayList<String>()
• `var` is not a keyword
– but a special type
• We can use `var` as a variable name
• We can use `var` as a method name
• We can not use `var` as a class name
13. Where can we use `var`?
• OK
– Right Oprand has the type
• var strs = new ArrayList<String>();
• var path = Path.of(“http://example.com”);
• Should not
– Enclosing type
• ex: Supplier<String>, Optional<String>
ListenableFuture<String>
• var name = findName(id);
print(name.get()); // How should we care?
14. Another usage for `var`
• Anonymous class become useful
– ex: defining a local method
• var m = new Object() {
int twice(int x) {
return x * 2;
}
};
print(m.twice(3));
15. 304: Garbage-Collector
Interface
• GC is modularized.
• There are many GCs that will come.
– Epsilon GC
– ZGC
– Shenandoah
• Not to control GC by user code
16. 317: Experimental Java-Based
JIT Compiler
• Project Metoropolis
– java-on-java
• We can write JVM even with Scala?
– There is a possibility.
17. 307: Parallel Full GC for G1
• G1GC had been the default GC on JDK
9
• Full GC for G1 was not parallel.
• Until JDK 8, Parallel GC was the
default
• To smooth migration, Full GC for
G1GC also parallelize.
• But full GC should not occur.
– Ideally, it has no effect for us.
18. 310: Application Class-Data
Sharing
• CDS for system class is introduced in
JDK 5
• Share class data between multiple
JVM
on the same machine
– startup performance
– reduce the resource footprint
• JDK 10 allow to use CDS for
application class
21. 314: Additional Unicode
Language-Tag Extensions
• Enhance java.util.Locale
• additional Unicode extensions
of BCP 47 language tag
– currency type
– the first day of the week
– region override
– time zone
22. 316: Heap Allocation on
Alternative Memory Devices
• Now we can use non-volatile RAM(不
揮発性メモリ) such as 3D XPoint
• This will enable the JVM to use
different types of memory system
23. 319: Root Certificates
• OpenJDK doesnʼt have Root
Certificates so far
• Oracle JDK have had it.
• To smooth migration, OpenJDK have
had it.
24. API Changes
• java.io.Reader
– long transferTo(Writer)
• java.lang.mainagement.RuntimeMXBe
an
– long getPid()
• java.util.List/Map/Set
– copyOf(Collection)
• java.util.stream.Collectors
– toUnmodifiableList/Set/Map
25. Docker aware
• Until JDK 9, JVM use the platform CPU
count/Memory size even if it is running
on Docker.
• JDK 10, JVM can use Docker setting for
CPU count/ Memory size if it is running
on Docker.
• VM Options
– -XX:InitialRAMPercentage
– -XX:MaxRAMPercentage
– -XX:MinRAMPercentage
26. Other Changes
• Kerberos configuration file krb5.conf
include *.conf in INCLUDEDIR
• -d32 and –d64 has been removed
• new JavaDoc tag. {@summary}
• policytool has been removed
• XMLInputFactory.newFactory() has
been “de-deprecated”
– it had been deprecated by mistake.
28. Java 11 JEPs
• 309 Dynamic Class-File Constants
• 318 Epsilon: A No-Op Garbage Collector
• 320 Remove the Java EE and CORBA Modules
• 321 HTTP Client(Standard)
• 323 Local-Variable Syntax for Lambda Parameters
• 324 Key Agreement with Curve25519 and Curve448
• 327 Unicode 10
• 328 Flight Recorder
• 329 ChaCha20 and Poly1305 Cryptographic Algorithms
• 330 Launch Single-File Source-Code Programs
29. Expected JEPs for JDK11
• 326 Raw String Literals
• 325 Switch Expressions
• 181 Nest-Based Access Control
30. Launch Single-File Source-Code
Programs
• java Hello.java
– The file name does not need to be related
with the class name
• Shebang
– #! /usr/bin/java –source 10
– chmod +x hello
– ./hello
31. Raw String Literals
• var sql = ```select NAME
from MEMBER
where id=1```
• var regexp = ```hello¥¥n```
// same as “hello¥¥¥¥n”
• How to address indent
32. Switch Expressions
• Now `switch` is a statement
• int i;
switch (s) {
case “start”:
case “begin”:
i = 0;
break;
case “end”:
i = 1;
break;
default:
i = 2;
44. API changes in JDK11
• String::repeat/lines/strip...
• Predicate::not
• Optional::isEmpty
• Files
• ArrayIndexOutOfBoundsException
– the message is changed
49. ArrayIndexOutOfBoundsException
• jshell> new int[]{}[0]
| java.lang.ArrayIndexOutOfBoundsException thrown: 0
| at (#1:1)
->
jshell> new int[]{}[0]
| Exception java.lang.ArrayIndexOutOfBoundsException:
Index 0 out of bounds for length 0
| at (#8:1)
50. How about Stream#toList?
• modifiable? unmodifiable?
• What order?
• “it nulls a property of the Stream API
we have take time to keep.
The whole Stream API doesn't
depends on the Collection API”
52. Oracle JDK
• Same as the current support
• Very expensive for web servicer
• 100 servers on AWS -> 1おくえん
53. OpenJDK
• Official publishment says it has only 6
months support for each JDK release.
No LTS
• Mark Reinhold said OpenJDK will have
LTS
– but not on the web site yet
– LTS support is for 3 years. No overlap.
54. AdoptOpenJDK
• Project by London JUG
• IBM supponsered
• Provide pre-build JDK
• LTS support for 4 years
55. Zulu
• Provided by Azul System
• Free to download and use
• Enterprise support
– 100 servers $28,750/year
– unlimited servers $258,750/year
56. Support the new era
after Heisei
• Start to support the new era as
NewEra
• JDK12 will release 2019/3
• The new era will release early 2019/4
• JDK maintenance release will be late
2019/4
– JDK 12.0.1
• The new era will start 2019/5