A presentation I did in IL Java User Group about Java 8, DateTime new features. JSR-310
I wanted it to be informative and a good resource and starting point for this cool feature.
This presentation provides an overview of using the Java SE 8 Date & Time API. It covers how to:
1. Create and manage date-based and time-based events including a combination of date and time into a single object using LocalDate, LocalTime, LocalDateTime, Instant, Period, and Duration
2. Work with dates and times across timezones and manage changes resulting from daylight savings including format date and times values
3. Define and create and manage date-based and time-based events using Instant, Period, Duration, and TemporalUnit
A code along session to introduce the java.time library in the upcoming release of Java 8. The materials to code along can be cloned from github here: https://github.com/jpgough/JavaTimeLab
This presentation provides an overview of using the Java SE 8 Date & Time API. It covers how to:
1. Create and manage date-based and time-based events including a combination of date and time into a single object using LocalDate, LocalTime, LocalDateTime, Instant, Period, and Duration
2. Work with dates and times across timezones and manage changes resulting from daylight savings including format date and times values
3. Define and create and manage date-based and time-based events using Instant, Period, Duration, and TemporalUnit
A code along session to introduce the java.time library in the upcoming release of Java 8. The materials to code along can be cloned from github here: https://github.com/jpgough/JavaTimeLab
Scala like distributed collections - dumping time-series data with apache sparkDemi Ben-Ari
Spark RDDs are almost identical to Scala collection, just in a distributed manner, all of the transformations and actions are derived from the Scala collections API.
As Martin Odersky mentioned, “Spark - The Ultimate Scala Collections” is the right way to look at RDDs. But with that great distributed power comes a great many data problems: at first you’ll start tackling the concept of partitioning, then the actual data becomes the next thing to worry about.
In the talk we’ll go through an overview on Spark's architecture, and see how similar RDDs are to the Scala collections API. We'll then shift to the world of problems that you’ll be facing when using Spark for processing a vast volume of time-series data with multiple data stores (S3, MongoDB, Apache Cassandra, MySQL).
When you start tackling many scale and performance problems, many questions arise:
> How to handle missing data?
> Should the system handle both serving and backend processes, or should we separate them out?
> Which solution is cheaper?
> How do we get the best performance for money spent?
In the talk we will tell the tale of all of the transformations we’ve made to our data and review the multiple data persistency layers... and I’ll try my best NOT to answer the question “which persistency layer is the best?” but I do promise to share our pains and lessons learned!
Abstract –
Spark 2 is here, while Spark has been the leading cluster computation framework for severl years, its second version takes Spark to new heights. In this seminar, we will go over Spark internals and learn the new concepts of Spark 2 to create better scalable big data applications.
Target Audience
Architects, Java/Scala developers, Big Data engineers, team leaders
Prerequisites
Java/Scala knowledge and SQL knowledge
Contents:
- Spark internals
- Architecture
- RDD
- Shuffle explained
- Dataset API
- Spark SQL
- Spark Streaming
Akka-demy (a.k.a. How to build stateful distributed systems) I/IIPeter Csala
This is the first part of a mini-series where we discuss how to build distributed stateful real-time applications using actor model and messaging.
The second part: https://www.slideshare.net/PeterCsala/akkademy-aka-how-to-build-stateful-distributed-systems-iiii
S3, Cassandra or Outer Space? Dumping Time Series Data using Spark - Demi Be...Codemotion
Vast volume of our processed data is Time Series data and once you start working with distributed systems, you start tackling many scale and performance problems: How to handle missing data?Should I handle both serving and backed process or separating them out? Best Performance for Money? In the talk we will tell the tale of all of the transformations we’ve made to our data model@Windward, some of the problems we’ve handled, review the multiple data persistency layers like: S3, MongoDB, Apache Cassandra, MySQL. And I’ll try my best NOT to answer the question “Which one of them is the Best?"
A presentation given to Overstock.com IT at annual conference. Twitter @TECHknO 2015. Goal of the presentation is to provide a good introduction to the reactive programming model with RxJava.
Surviving as a zombie is tough... with the constant risks of sunlight, fire, and pesky mobs, doing your job of infecting the local villagers can be deadly. Fortunately, with the new JavaFX ZombieTime app, powered by the JSR 310 Date and Time API, you can rest easy. With built-in time zone and DST support you no longer have to worry about roaming around under the scorching hot sun. Accurately calculate out how long you have to infect the villagers before you decompose using Durations. And coordinate global attacks on the humans by syncing with your undead brethren on Instants. With the power of Java 8, eradicating the human race with a highly infectious virus has never been easier!
This presentation is designed to teach Java Date and Time APIs to the undead, but the living are welcome to be our "guests". You may also learn some JavaFX in the process -- that is entirely my fault. Any correlation between the characters and events in this presentation and the impending extinction of mankind is purely coincidental.
Scala like distributed collections - dumping time-series data with apache sparkDemi Ben-Ari
Spark RDDs are almost identical to Scala collection, just in a distributed manner, all of the transformations and actions are derived from the Scala collections API.
As Martin Odersky mentioned, “Spark - The Ultimate Scala Collections” is the right way to look at RDDs. But with that great distributed power comes a great many data problems: at first you’ll start tackling the concept of partitioning, then the actual data becomes the next thing to worry about.
In the talk we’ll go through an overview on Spark's architecture, and see how similar RDDs are to the Scala collections API. We'll then shift to the world of problems that you’ll be facing when using Spark for processing a vast volume of time-series data with multiple data stores (S3, MongoDB, Apache Cassandra, MySQL).
When you start tackling many scale and performance problems, many questions arise:
> How to handle missing data?
> Should the system handle both serving and backend processes, or should we separate them out?
> Which solution is cheaper?
> How do we get the best performance for money spent?
In the talk we will tell the tale of all of the transformations we’ve made to our data and review the multiple data persistency layers... and I’ll try my best NOT to answer the question “which persistency layer is the best?” but I do promise to share our pains and lessons learned!
Abstract –
Spark 2 is here, while Spark has been the leading cluster computation framework for severl years, its second version takes Spark to new heights. In this seminar, we will go over Spark internals and learn the new concepts of Spark 2 to create better scalable big data applications.
Target Audience
Architects, Java/Scala developers, Big Data engineers, team leaders
Prerequisites
Java/Scala knowledge and SQL knowledge
Contents:
- Spark internals
- Architecture
- RDD
- Shuffle explained
- Dataset API
- Spark SQL
- Spark Streaming
Akka-demy (a.k.a. How to build stateful distributed systems) I/IIPeter Csala
This is the first part of a mini-series where we discuss how to build distributed stateful real-time applications using actor model and messaging.
The second part: https://www.slideshare.net/PeterCsala/akkademy-aka-how-to-build-stateful-distributed-systems-iiii
S3, Cassandra or Outer Space? Dumping Time Series Data using Spark - Demi Be...Codemotion
Vast volume of our processed data is Time Series data and once you start working with distributed systems, you start tackling many scale and performance problems: How to handle missing data?Should I handle both serving and backed process or separating them out? Best Performance for Money? In the talk we will tell the tale of all of the transformations we’ve made to our data model@Windward, some of the problems we’ve handled, review the multiple data persistency layers like: S3, MongoDB, Apache Cassandra, MySQL. And I’ll try my best NOT to answer the question “Which one of them is the Best?"
A presentation given to Overstock.com IT at annual conference. Twitter @TECHknO 2015. Goal of the presentation is to provide a good introduction to the reactive programming model with RxJava.
Surviving as a zombie is tough... with the constant risks of sunlight, fire, and pesky mobs, doing your job of infecting the local villagers can be deadly. Fortunately, with the new JavaFX ZombieTime app, powered by the JSR 310 Date and Time API, you can rest easy. With built-in time zone and DST support you no longer have to worry about roaming around under the scorching hot sun. Accurately calculate out how long you have to infect the villagers before you decompose using Durations. And coordinate global attacks on the humans by syncing with your undead brethren on Instants. With the power of Java 8, eradicating the human race with a highly infectious virus has never been easier!
This presentation is designed to teach Java Date and Time APIs to the undead, but the living are welcome to be our "guests". You may also learn some JavaFX in the process -- that is entirely my fault. Any correlation between the characters and events in this presentation and the impending extinction of mankind is purely coincidental.
MetaScale Case Study: Hadoop Extends DataStage ETL CapacityMetaScale
Knowing how to mix hardware with proprietary and open source software can lead to improved performance and reduced costs, as a MetaScale team showed with a client who was running out of capacity using IBM DataStage for ETL.
Media owners are turning to MongoDB to drive social interaction with their published content. The way customers consume information has changed and passive communication is no longer enough. They want to comment, share and engage with publishers and their community through a range of media types and via multiple channels whenever and wherever they are. There are serious challenges with taking this semi-structured and unstructured data and making it work in a traditional relational database. This webinar looks at how MongoDB’s schemaless design and document orientation gives organisation’s like the Guardian the flexibility to aggregate social content and scale out.
Using The Internet of Things for Population Health Management - StampedeCon 2016StampedeCon
The Internet of (Human) Things is just beginning to take shape. The human body is an inexhaustible source of data about personal health, and the healthcare industry is just beginning to scratch the surface of the potential insights and value that will come from that data. While much of healthcare traditionally focuses on the episodic delivery of services, the Affordable Care Act is pushing healthcare providers, payers, and self-funded employer groups to look at ways to proactively encourage healthy behaviors. Providing personal health devices as a way to promote individual health is one way that healthcare is beginning to take advantage of IoT technologies. This session provides insight into how IoT is being leveraged in population health management through a solution jointly delivered by Amitech Solutions and Big Cloud Analytics. Attendees will learn how Hadoop is being used to gather personal device from various vendors, integrate and analyze that information, differentiate trends across regional and cultural diversity, and provide personal recommendations and insights into health risks. This session presents one important way the healthcare industry is leveraging IoT.
Slides for a lightning talk on HBase that I gave at Near Infinity (www.nearinfinity.com) spring 2012 conference.
The associated sample code is on GitHub at https://github.com/sleberknight/basic-hbase-examples
Workshop
December 9, 2015
LBS College of Engineering
www.sarithdivakar.info | www.csegyan.org
http://sarithdivakar.info/2015/12/09/wordcount-program-in-python-using-apache-spark-for-data-stored-in-hadoop-hdfs/
Hadoop Interview Questions and Answers by rohit kapakapa rohit
Hadoop Interview Questions and Answers - More than 130 real time questions and answers covering hadoop hdfs,mapreduce and administrative concepts by rohit kapa
IoT and Edge Integration with Open Source Frameworks:
Internet of Things (IoT) and edge integration is getting more important than ever before due to the massively growing number of connected devices year by year.
This session shows open source frameworks built to develop very lightweight microservices, which can be deployed on small devices or in serverless architectures with very low resources and wire together all different kinds of hardware devices, APIs and online services.
The focus of this session lies on showing open source projects such as Eclipse Kura, Node-RED or Flogo, which offer a framework plus zero-code environment with web IDE for building and deploying integration and data processing directly onto connected devices using IoT standards such as MQTT, WebSockets or CoaP, but also other interfaces such as Twitter feeds or REST services.
The end of the session discusses the relation to other components in a IoT architecture including cloud IoT platforms and big data respectively streaming analytics solutions (such as Apache Storm, Flink, Spark Streaming, Samza, StreamBase, Apama).
Compression Options in Hadoop - A Tale of TradeoffsDataWorks Summit
Yahoo! is one of the most-visited web sites in the world. It runs one of the largest private cloud infrastructures, one that operates on petabytes of data every day. Being able to store and manage that data well is essential to the efficient functioning of Yahoo!`s Hadoop clusters. A key component that enables this efficient operation is data compression. With regard to compression algorithms, there is an underlying tension between compression ratio and compression performance. Consequently, Hadoop provides support for several compression algorithms, including gzip, bzip2, Snappy, LZ4 and others. This plethora of options can make it difficult for users to select appropriate codecs for their MapReduce jobs. This paper attempts to provide guidance in that regard. Performance results with Gridmix and with several corpuses of data are presented. The paper also describes enhancements we have made to the bzip2 codec that improve its performance. This will be of particular interest to the increasing number of users operating on “Big Data” who require the best possible ratios. The impact of using the Intel IPP libraries is also investigated; these have the potential to improve performance significantly. Finally, a few proposals for future enhancements to Hadoop in this area are outlined.
MODELS 2019: Querying and annotating model histories with time-aware patternsAntonio García-Domínguez
30 minute slides for our talk at the IEEE / ACM 22nd International Conference on Model Driven Engineering Languages and Systems conference, on our Eclipse Hawk model indexing tool.
Time Series Analytics with Spark: Spark Summit East talk by Simon OuelletteSpark Summit
spark-timeseries is a Scala / Java / Python library for interacting with time series data on Apache Spark.
Time-series are an important part of data science applications, but are notoriously difficult in the context of distributed systems, due to their sequential nature. Getting this right is therefore a challenging but important element of progress in the universe of distributed systems applied to data science.
This talk will cover the current overall design of spark-timeseries, the current functionalities, and will provide some usage examples. Because the project is still at an early stage, the talk will also cover the current weaknesses and future improvements that are in the spark-timeseries project roadmap.
"Эффективность и оптимизация кода в Java 8" Сергей МоренецFwdays
Если мы захотим понять, что такое совершенный(идеальный) код, то одной из его характеристик будет эффективность. Это включает в себя и быстродействие кода, и объем потребляемых ресурсов(память, дисковых, I/O).
Зачастую эффективность отодвигается на второй план, поскольку ее не так просто рассчитать заранее, а также точно определить на ревью кода. В то же время это единственная характеристика, которая затрагивает конечного пользователя наших проектов.
В моем докладе я рассмотрю, что такое эффективность, как ее правильно измерять, мы коснемся мифов об эффективности, которые очень популярны сейчас, рассмотрим примеры эффективного и неэффективного кода, нужной и бессмысленной оптимизации кода.
Главный упор будет сделан на функциональности, которая была добавлена в Java 8.
Libraries and History
The “old” Date/Calendar classes
The new (≥Java8) java.time package
Basic concepts
Main classes
Date operations
Dealing with SQL dates
Teaching material for the course of "Tecniche di Programmazione" at Politecnico di Torino in year 2014/2015. More information: http://bit.ly/tecn-progr
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."
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
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.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Top 7 Unique WhatsApp API Benefits | Saudi ArabiaYara Milbes
Discover the transformative power of the WhatsApp API in our latest SlideShare presentation, "Top 7 Unique WhatsApp API Benefits." In today's fast-paced digital era, effective communication is crucial for both personal and professional success. Whether you're a small business looking to enhance customer interactions or an individual seeking seamless communication with loved ones, the WhatsApp API offers robust capabilities that can significantly elevate your experience.
In this presentation, we delve into the top 7 distinctive benefits of the WhatsApp API, provided by the leading WhatsApp API service provider in Saudi Arabia. Learn how to streamline customer support, automate notifications, leverage rich media messaging, run scalable marketing campaigns, integrate secure payments, synchronize with CRM systems, and ensure enhanced security and privacy.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
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?
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.
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...Crescat
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
A Study of Variable-Role-based Feature Enrichment in Neural Models of CodeAftab Hussain
Understanding variable roles in code has been found to be helpful by students
in learning programming -- could variable roles help deep neural models in
performing coding tasks? We do an exploratory study.
- These are slides of the talk given at InteNSE'23: The 1st International Workshop on Interpretability and Robustness in Neural Software Engineering, co-located with the 45th International Conference on Software Engineering, ICSE 2023, Melbourne Australia
12. Example – The New Way
12
Today 2014-07-29 and next year 2015-07-29
13. Modeling
• Different date/time scenarios
• Class starts at 12:30
• ilJUG is on 29th July
• The presentation is 1 hour long
• I’ve been working at eBay for 3 years and 6
months
13
17. Amount of Time
• How many milliseconds it took
between request to response?
• Set time 10 seconds after now
• Calculate time that passed between
two events
17
18. Example – Old Calculation
18
now Tue Jul 29 01:48:56 IDT 2014 and later Thu Jan 01 04:20:00 IST 1970
19. Example – Old Calculation
19
119 days 6 hours 13 minutes 24 seconds 543 ms
Example taken from stackoverflow
24. Guidelines
• Clear
• Fluent
• DSL
• Immutability
• Amount of time, different
representations for different cases
• Human (year, month, day)
• Machine time
24
26. Some (not all) Classes
• Temporal – Basic interface for DateTime classes
• LocalDate / LocalTime / LocalDateTime …
• Instant
• Start of nanoseconds in timeline. Useful for timestamp
• Clock
• Allowing Temporal creation with alternate clock
• TemporalAmount – Basic interface for classes
that represent amount of time
• Duration
• Period
26
27. Methods Naming Conventions
of Static Creates an instance with validation
to Instance Converts to another type (truncate fields)
at Instance Combines this object with another
(expands)
from Static Converts input parameters to an instance
get Instance Part of the state of the object
27
28. Methods Naming Conventions
is Instance Queries state of an object
with Instance Returns a copy of an object with one
changed element
plus /
minus
instance Returns a copy of an object with amount of
added / subtracted time
parse Static Parses input string to an instance
format Instance Uses formatter to format the object’s values
to produce a string
28
41. Instant
41
From Javadoc:
"This class models a single instantaneous point on the time-line.
This might be used to record event time-stamps in the application...
"...number of seconds that can be held in a long. This is greater than the current
estimated age of the universe...
"...The instant is stored to nanosecond resolution..."
42. Adjusters
• Take Temporal value and adjust it
• Pre defined
• firstDayOfMonth
• firstDayOfYear
• lastInMonth
• Look at TemoralAdjusters
• Custom adjusters
42
48. Parsing and Formatting
• DateTimeFormatter
• Many pre defined formats
• http://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html#predefined
• Immutable
• DateTimeFormatterBuilder
• All classes use the same way
• DateTimeParseException (runtime)
48