Igor Anishchenko
Odessa Java TechTalks
Lohika - September, 2012
This session starts with a high-level look at all that the Spring Data project has to offer.
Then we’ll dive deeper into a few select Spring Data modules, including Spring Data JPA, Spring Data MongoDB and Spring Data Redis.
Implementing a data access layer of an application has been cumbersome for quite a while. Too much boilerplate code had to be written!
Spring Data is a project that makes it easier to build Spring-powered applications that use new data, offering a reasonably consistent programming model regardless of which type of database you choose.
In addition to supporting the new “NoSQL” databases such as document and graph databases, Spring Data also greatly simplifies working with RDBMS-oriented datastores using JPA -simplifies the development of creating a JPA-based data access layer.
Spring Data is a high level SpringSource project whose purpose is to unify and ease the access to different kinds of persistence stores, both relational database systems and NoSQL data stores.
Hibernate 3: Hibernate-What it is ?, ORM and Issues, Hibernate Hello World CRUD, Hello world with Servlet, Hibernate Object life cycle, Hibernate Architecture, Object as Component mapping, Hibernate Inheritance, Hibernate Unidirectional Mapping, Hibernate Bidirectional mapping, HQL, Native SQL queries, Named Quarries
Spring Data is a high level SpringSource project whose purpose is to unify and ease the access to different kinds of persistence stores, both relational database systems and NoSQL data stores.
Hibernate 3: Hibernate-What it is ?, ORM and Issues, Hibernate Hello World CRUD, Hello world with Servlet, Hibernate Object life cycle, Hibernate Architecture, Object as Component mapping, Hibernate Inheritance, Hibernate Unidirectional Mapping, Hibernate Bidirectional mapping, HQL, Native SQL queries, Named Quarries
A powerful ORM tool to design data base access layer.
Fills gaps of mismatches between OOPs and RDBMS paradigm. Also maintains adequate ultra performance of database access.
An automated, configurable persistence of java objects with tables in data base.
May not be a good solution for data-centric application which uses only stored procedures to implement business logic in the database.
Java Hibernate Programming with Architecture Diagram and Examplekamal kotecha
Java Hibernate Introduction, Architecture and Example with step by step guidance to run the program especially for students and teachers.
Learn More @ http://java2all.com/technology/hibernate
TUTORIAL-INTRODUCTION TO SPRING FOR BEGINNERS
EXPLANATION TO-Java Framework,Advantages of using SPRING,Difference between Hibernate and Spring.Spring architecture,Spring IoC Containters,Bean scope & Method Injection,Spring Inheritance.
In this core java training session, you will learn Java IO – Files, Streams and
Object Serialization. Topics covered in this session are:
• Java IO
• Files
• Streams
• Byte-based
• Character-based
• Object Serialization
For more information about this course visit on this link: https://www.mindsmapped.com/courses/software-development/learn-java-fundamentals-hands-on-training-on-core-java-concepts/
Entity Framework, Code First, Database First, TPH, TPT, TPC. Table Per Type, Table Per Hierarchy, Table Per Concrete Class, EF Concurrency, EF Relationship, Code First Conventions
A hibernate tutorial for beginners. It describe the hibernate concepts in a lucid manner and and test project(User application with database) to get hands on over the same.
Introduction to JPA and Hibernate including examplesecosio GmbH
In this talk, held as part of the Web Engineering lecture series at Vienna University of Technology, we introduce the main concepts of Java Persistence API (JPA) and Hibernate.
The first part of the presentation introduces the main principles of JDBC and outlines the major drawbacks of JDBC-based implementations. We then further outline the fundamental principles behind the concept of object relation mapping (ORM) and finally introduce JPA and Hibernate.
The lecture is accompanied by practical examples, which are available on GitHub.
Core Data can be intimidating at first. With a proper introduction, the transition into using Core Data can be much smoother. This presentation gives an overview of the core and advanced parts of Core Data.
Java and Spring Data JPA: Easy SQL Data Access
Abstract
Presenter: Miya W. Longwe, MBA, MSE, Tech Lead, Staples, Inc, Framingham MA 01702
Accessing data repositories in various applications programming languages typically involves writing of tedious boilerplate lines of code. Some application development frameworks such as Spring have tried to make the experience more succinct by providing abstraction layers such as HibernateTemplate and JdbcTemplate, etc. Despite these APIs, the developers still spend a lot time writing repetitive code than concentrating on implementing business requirements. Developers at Spring, led by Oliver Gierke, introduced Spring Data JPA which “aims to significantly improve the implementation of data access layers by reducing the effort to the amount that's actually needed. As a developer you write your repository interfaces, including custom finder methods, and Spring will provide the implementation automatically”.
Spring Data JPA provides a powerful, out-of-the-box alternative to creating your own DAO framework. You declare custom repository operations on an interface, and the framework generates dynamic implementations (not code generation) automatically, based on conventions around method names. As part of the presentation, we'll also review a demo to look at Spring Java configuration (as opposed to XML configuration), and investigate the @Profile annotation – configuration details which may make life a bit easier in various ways when setting up unit testing of our repository classes, using out-of-the-box alternative to creating DAO framework, how to create custom repositories, pagination and support for custom queries among other features.
Presenter's Bio
Miya W. Longwe is a Senior Software Engineer and Tech Lead at Staples, Inc. where he is currently working on an initiative to re-platform the company’s ecommerce architecture to offer platform-driven, modular products that can be quickly customized, enhanced, and branded as needed.
Miya has been a software professional since 1997. His 16 years software development career includes working for large companies to small startups, building solutions for enterprises and consumers, working with a broad range of technologies.
Miya Longwe is a hands-on java developer. He believes that in order to be a relevant and effective software developer one needs to remain a deeply knowledgeable, up-to-date, and productive software developer. His research interests include model-driven engineering, domain specific languages, test driven development and project risk management.
Miya graduated from the University of Malawi (Lilongwe, Malawi) and has an MBA from the University of Wales Cardiff Business School (Wales, UK) and a Masters in Software Engineering from Brandeis University (MA, USA).
Occasionally, Miya can be spotted fishing the banks of the south shore (MA) with his two boys, William and Daniel.
A powerful ORM tool to design data base access layer.
Fills gaps of mismatches between OOPs and RDBMS paradigm. Also maintains adequate ultra performance of database access.
An automated, configurable persistence of java objects with tables in data base.
May not be a good solution for data-centric application which uses only stored procedures to implement business logic in the database.
Java Hibernate Programming with Architecture Diagram and Examplekamal kotecha
Java Hibernate Introduction, Architecture and Example with step by step guidance to run the program especially for students and teachers.
Learn More @ http://java2all.com/technology/hibernate
TUTORIAL-INTRODUCTION TO SPRING FOR BEGINNERS
EXPLANATION TO-Java Framework,Advantages of using SPRING,Difference between Hibernate and Spring.Spring architecture,Spring IoC Containters,Bean scope & Method Injection,Spring Inheritance.
In this core java training session, you will learn Java IO – Files, Streams and
Object Serialization. Topics covered in this session are:
• Java IO
• Files
• Streams
• Byte-based
• Character-based
• Object Serialization
For more information about this course visit on this link: https://www.mindsmapped.com/courses/software-development/learn-java-fundamentals-hands-on-training-on-core-java-concepts/
Entity Framework, Code First, Database First, TPH, TPT, TPC. Table Per Type, Table Per Hierarchy, Table Per Concrete Class, EF Concurrency, EF Relationship, Code First Conventions
A hibernate tutorial for beginners. It describe the hibernate concepts in a lucid manner and and test project(User application with database) to get hands on over the same.
Introduction to JPA and Hibernate including examplesecosio GmbH
In this talk, held as part of the Web Engineering lecture series at Vienna University of Technology, we introduce the main concepts of Java Persistence API (JPA) and Hibernate.
The first part of the presentation introduces the main principles of JDBC and outlines the major drawbacks of JDBC-based implementations. We then further outline the fundamental principles behind the concept of object relation mapping (ORM) and finally introduce JPA and Hibernate.
The lecture is accompanied by practical examples, which are available on GitHub.
Core Data can be intimidating at first. With a proper introduction, the transition into using Core Data can be much smoother. This presentation gives an overview of the core and advanced parts of Core Data.
Java and Spring Data JPA: Easy SQL Data Access
Abstract
Presenter: Miya W. Longwe, MBA, MSE, Tech Lead, Staples, Inc, Framingham MA 01702
Accessing data repositories in various applications programming languages typically involves writing of tedious boilerplate lines of code. Some application development frameworks such as Spring have tried to make the experience more succinct by providing abstraction layers such as HibernateTemplate and JdbcTemplate, etc. Despite these APIs, the developers still spend a lot time writing repetitive code than concentrating on implementing business requirements. Developers at Spring, led by Oliver Gierke, introduced Spring Data JPA which “aims to significantly improve the implementation of data access layers by reducing the effort to the amount that's actually needed. As a developer you write your repository interfaces, including custom finder methods, and Spring will provide the implementation automatically”.
Spring Data JPA provides a powerful, out-of-the-box alternative to creating your own DAO framework. You declare custom repository operations on an interface, and the framework generates dynamic implementations (not code generation) automatically, based on conventions around method names. As part of the presentation, we'll also review a demo to look at Spring Java configuration (as opposed to XML configuration), and investigate the @Profile annotation – configuration details which may make life a bit easier in various ways when setting up unit testing of our repository classes, using out-of-the-box alternative to creating DAO framework, how to create custom repositories, pagination and support for custom queries among other features.
Presenter's Bio
Miya W. Longwe is a Senior Software Engineer and Tech Lead at Staples, Inc. where he is currently working on an initiative to re-platform the company’s ecommerce architecture to offer platform-driven, modular products that can be quickly customized, enhanced, and branded as needed.
Miya has been a software professional since 1997. His 16 years software development career includes working for large companies to small startups, building solutions for enterprises and consumers, working with a broad range of technologies.
Miya Longwe is a hands-on java developer. He believes that in order to be a relevant and effective software developer one needs to remain a deeply knowledgeable, up-to-date, and productive software developer. His research interests include model-driven engineering, domain specific languages, test driven development and project risk management.
Miya graduated from the University of Malawi (Lilongwe, Malawi) and has an MBA from the University of Wales Cardiff Business School (Wales, UK) and a Masters in Software Engineering from Brandeis University (MA, USA).
Occasionally, Miya can be spotted fishing the banks of the south shore (MA) with his two boys, William and Daniel.
JPA as Tools for an Object Oriented Domain Modell using Hibernate as JPA Vendor. Presentation was held on customer site in Berlin and transmitted to the Lünen Office.
Java Persistence API (JPA) - A Brief OverviewCraig Dickson
This is a lightning presentation given by Scott Rabon, a member of my development team. He presents a high level overview of the JPA based on his first exposure to it.
What is tackled in the Java EE Security API (Java EE 8)Rudy De Busscher
The Java EE Security API (JSR-375) wants to simplify the implementation of security-related features in your Java EE application. Application server specific configuration changes will be no longer needed and things will be much more app developer friendly. Aligning security with the ease of development we saw in the recent version of Java EE. We will show you the basic goals and concepts behind Java EE Security API. And of course, demos with the current version of the RI, named Soteria, how you can do Authentication and Authorization.
Java Developers, make the database work for you (NLJUG JFall 2010)Lucas Jellema
The general consensus among Java developers has evolved from a dogmatic strive for database independence to a much more pragmatic wish to leverage the power of the database. This session demonstrates some of the (hidden) powers of the database and how these can be utilized from Java applications using either straight JDBC or working through JPA. The Oracle database is used as example: SQL for Aggregation and Analysis, Flashback Queries for historical comparison and trends, Virtual Private Database, complex validation, PL/SQL and collections for bulk data manipulation, view and instead-of triggers for data model morphing, server push of relevant data changes, edition based redefinition for release management.
- overview of role of database in JEE architecture (and a little history on how the database is perceived through the years)
- discussion on the development of database functionality
- demonstration of some powerful database features
- description of how we leveraged these features in our JSF (RichFaces)/JPA (Hibernate) application
- demo of web application based on these features
- discussion on how to approach the database
AngularJS 1.x - your first application (problems and solutions)Igor Talevski
We will talk about all aspects of building a single page application with AngularJS, and we will discuss real examples from day-to-day work. We will also cover a large amount of theory about general web development, best practices, and today's client demands. We will focus on three (3) main points: architecture, security, and real time notification.
ГАННА КАПЛУН «noSQL vs SQL: порівняння використання реляційних та нереляційни...QADay
Kyiv Quality Assurance Day 2021
ГАННА КАПЛУН
«noSQL vs SQL: порівняння використання реляційних та нереляційних СУБД в комерційних програмах»
Слідкуйте за нами:
Телеграм: t.me/goqameetup
Linkedin: linkedin.com/company/goqa
Fb: https://www.facebook.com/goqaevent
Fb: https://www.facebook.com/qaday.org
Youtube: https://www.youtube.com/channel/UCOyIrmpVbtqUZyRLxd9BKzA
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
12. Mongo data model
A Mongo system (see deployment above) holds a set
of databases
A database holds a set of collections
A collection holds a set of documents
A document is a set of fields
A field is a key-value pair
A key is a name (string)
A value is a
basic type like
string, integer, float, timestamp, binary, etc.,
a document, or
an array of values
13. MongoDB
• Flexible data model
• Data can be inserted without a defined schema, and
the format of the data being inserted can change
at any time
• Easy scalability
• Databases automatically spreads data across
servers, requiring no participation from the
applications.
• Servers can be added and removed without downtime
17. " This document is the specification of the
Java API for the management of persistence
and object/relational mapping with Java EE
and Java SE. The technical objective of this
work is to provide an object/relational
mapping facility for the Java application
developer using a Java domain model to man-
age a relational database.
18. " This document is the specification of the
Java API for the management of persistence
and object/relational mapping with Java
EE and Java SE. The technical objective of
this work is to provide an
object/relational mapping facility for
the Java application developer using a Java
domain model to man- age a relational
database.
22. Mission statement
“… provides a familiar and
consistent Spring-based programming
model for NoSQL and relational stores
while retaining store-specific
features and capabilities”
23. ... history
• The Spring Data project was coined at 2010
• Originated by Rod Johnson (SpringSource)
and Neo Technologies) early that year
• They were trying to integrate the Neo4j
graph database with the Spring framework
and evaluated different approaches
• Current version
24. Spring Data
JDBC JPA
support for relational stores...
25. Spring Data
JDBC JPA
support for relational stores...
26. Spring Data
JDBC JPA
support for relational stores...
27. Spring Data
JDBC JPA
support for relational stores...
28. Spring Data
JDBC JPA
support for relational stores...
30. Spring Core
• IoC/DI
• Spring namespace
• Configuring resources to access the stores
• Integration with core Spring functionality
like JMX is provided which means that some
stores will expose statistics through their
native API
32. ...Mapping
• A very core part of the Spring Data modules is a
mapping and conversion API that allows obtaining
meta-data about domain classes
• Most of the NoSQL Java APIs do not provide support
to map domain objects onto the stores data
abstractions
• With native Java drivers You would usually have to
write a significant amount of code to map data
onto your domain objects
36. ... Templates
• Heavily used in spring (JdbcTemplate, JmsTemplate)
• JdbcTemplate - simplifies the use of JDBC and helps to:
• avoid common errors
• executes core JDBC workflow
• SQL queries or updates, iteration over ResultSets and
• catching JDBC exceptions
• Spring takes this concept and provided templates for noSQL
stores
• RedisTemplate
• MongoTemplate
• Offer helper methods that allow us to execute commonly needed
operations like persisting an object with a single statement while
automatically taking care of appropriate resource management and
exception translation
41. ... Repositories
• Provides a repository abstraction on top of the Template
implementation
• Will reduce the effort to implement data access objects to a
plain interface definition for the most common scenarios like
standard CRUD operations as well as executing queries in case
the store supports that.
• This abstraction is actually the most top layer and blends
the APIs of the different stores as much as reasonably
possible.
• Interface based programming model, so you have an interface
for the queries you want to trigger and then those methods
will be generated without a need to implement this interface
Scaling is the problem - http://prabhubuzz.wordpress.com/2010/09/06/not-only-sql/ move to the cloud made things worse RDBS don't scale easily into the horizontal manner.
many noSql vendorsStrong ConsistencyAll clients see the same view, even in presence of updatesHigh AvailabilityAll clients can find some replica of the data, even in the presence of failuresPartition-toleranceThe system properties hold even when the system is partitionedThe CAP theorem states that you can always have only two of the above three CAP properties. The ACID system serves consistency. Hence Amazon Dynamo providing Availability and Partitioning properties, consistency is eventually achieved.
Columns families - cassandra (scale much better) table of column families
Key Value stores (redis) - like HashMapRedis, Riak, Project Voldemort, Membase, Amazon SimpleDB, Amazon Dynamo, MemcachedDB
Documents store (jason stores) - mongoDB, CouchDb,RavenDB, JackRabbit, Terrastore - i will show in a few minutesMongoDB Infrastructure APIMongoDB Query API
so much choices, so many APIs - they are very different, not all of the those stores have Java driversfrom Java developers perspective, how can we approach this, how Java developer can get easy access to those stores, without drill down to all the details of the stores.
Spring Data makes it easier to build Spring-powered applications that use new data access technologies such as non-relational databases, map-reduce frameworks, and cloud based data services as well as provide improved support for relational database technologies.Spring Data is an umbrella open source project which contains many subprojects that are specific to a given database. The projects are developed by working together with many of the companies and developers that are behind these exciting technologies.
Spring Data supported modules - pics: key value stores - riak, redis (vmware product, not surprise) documents - mongodb, couchbase (active development is on mongodb)hadoop (big data manipulation), neo4j support for relational stores: JDBC and JPA (consists only a repository)
Spring Data supported modules - pics: key value stores - riak, redis (vmware product, not surprise) documents - mongodb, couchbase (active development is on mongodb)hadoop (big data manipulation), neo4j support for relational stores: JDBC and JPA (consists only a repository)
Spring Data supported modules - pics: key value stores - riak, redis (vmware product, not surprise) documents - mongodb, couchbase (active development is on mongodb)hadoop (big data manipulation), neo4j support for relational stores: JDBC and JPA (consists only a repository)
Spring Data supported modules - pics: key value stores - riak, redis (vmware product, not surprise) documents - mongodb, couchbase (active development is on mongodb)hadoop (big data manipulation), neo4j support for relational stores: JDBC and JPA (consists only a repository)
Spring Data supported modules - pics: key value stores - riak, redis (vmware product, not surprise) documents - mongodb, couchbase (active development is on mongodb)hadoop (big data manipulation), neo4j support for relational stores: JDBC and JPA (consists only a repository)
http://www.infoq.com/articles/spring-data-intro
A very core theme of the Spring Data project available through all of the stores is support for configuring resources to access the stores. This supported is mainly implemented as XML namespace and support classes for Spring JavaConfig and will allow us to easily setup access to a MongoDB, an embedded Neo4j instance and the like. Also integration with core Spring functionality like JMX is provided which means that some stores will expose statistics through their native API which will be exposed to JMX via Spring Data.
Most of the NoSQL Java APIs do not provide support to map domain objects onto the stores data abstractions (documents in MongoDB, nodes and relationships for Neo4j). So when working with the native Java drivers you would usually have to write a significant amount of code to map data onto your domain objects of your application when reading and vice versa on writing. Thus, a very core part of the Spring Data modules is a mapping and conversion API that allows obtaining meta-data about domain classes to be persistent as well as the actual conversion of arbitrary domain objects into store specific data types.
Most of the NoSQL Java APIs do not provide support to map domain objects onto the stores data abstractions (documents in MongoDB, nodes and relationships for Neo4j). So when working with the native Java drivers you would usually have to write a significant amount of code to map data onto your domain objects of your application when reading and vice versa on writing. Thus, a very core part of the Spring Data modules is a mapping and conversion API that allows obtaining meta-data about domain classes to be persistent as well as the actual conversion of arbitrary domain objects into store specific data types.
Most of the NoSQL Java APIs do not provide support to map domain objects onto the stores data abstractions (documents in MongoDB, nodes and relationships for Neo4j). So when working with the native Java drivers you would usually have to write a significant amount of code to map data onto your domain objects of your application when reading and vice versa on writing. Thus, a very core part of the Spring Data modules is a mapping and conversion API that allows obtaining meta-data about domain classes to be persistent as well as the actual conversion of arbitrary domain objects into store specific data types.
Most of the NoSQL Java APIs do not provide support to map domain objects onto the stores data abstractions (documents in MongoDB, nodes and relationships for Neo4j). So when working with the native Java drivers you would usually have to write a significant amount of code to map data onto your domain objects of your application when reading and vice versa on writing. Thus, a very core part of the Spring Data modules is a mapping and conversion API that allows obtaining meta-data about domain classes to be persistent as well as the actual conversion of arbitrary domain objects into store specific data types.
any one knows jdbctemplate in spring? Its heavily used in spring. This is the central class in the JDBC core package. This is the class that provides an API. It simplifies the use of JDBC and helps to avoid common errors. It executes core JDBC workflow, leaving application code to provide SQL and extract results. This class executes SQL queries or updates, initiating iteration over ResultSets and catching JDBC exceptions and translating them to the generic, more informative exception hierarchy defined in the org.springframework.dao package. Spring takes this concept and provided templates for noSQL stores you can find MongoTemplate, RedisTemplateOn top of that we'll find opinionated APIs in the shape of template pattern implementations already well known from Spring's JdbcTemplate, JmsTemplate etc. Thus, there is a RedisTemplate, a MongoTemplate and so on. As you probably already know these templates offer helper methods that allow us to execute commonly needed operations like persisting an object with a single statement while automatically taking care of appropriate resource management and exception translation. Beyond that they expose callback APIs that allow you to access the store native APIs while still getting exceptions translated and resources managed properly.
any one knows jdbctemplate in spring? Its heavily used in spring. This is the central class in the JDBC core package. This is the class that provides an API. It simplifies the use of JDBC and helps to avoid common errors. It executes core JDBC workflow, leaving application code to provide SQL and extract results. This class executes SQL queries or updates, initiating iteration over ResultSets and catching JDBC exceptions and translating them to the generic, more informative exception hierarchy defined in the org.springframework.dao package. Spring takes this concept and provided templates for noSQL stores you can find MongoTemplate, RedisTemplateOn top of that we'll find opinionated APIs in the shape of template pattern implementations already well known from Spring's JdbcTemplate, JmsTemplate etc. Thus, there is a RedisTemplate, a MongoTemplate and so on. As you probably already know these templates offer helper methods that allow us to execute commonly needed operations like persisting an object with a single statement while automatically taking care of appropriate resource management and exception translation. Beyond that they expose callback APIs that allow you to access the store native APIs while still getting exceptions translated and resources managed properly.
any one knows jdbctemplate in spring? Its heavily used in spring. This is the central class in the JDBC core package. This is the class that provides an API. It simplifies the use of JDBC and helps to avoid common errors. It executes core JDBC workflow, leaving application code to provide SQL and extract results. This class executes SQL queries or updates, initiating iteration over ResultSets and catching JDBC exceptions and translating them to the generic, more informative exception hierarchy defined in the org.springframework.dao package. Spring takes this concept and provided templates for noSQL stores you can find MongoTemplate, RedisTemplateOn top of that we'll find opinionated APIs in the shape of template pattern implementations already well known from Spring's JdbcTemplate, JmsTemplate etc. Thus, there is a RedisTemplate, a MongoTemplate and so on. As you probably already know these templates offer helper methods that allow us to execute commonly needed operations like persisting an object with a single statement while automatically taking care of appropriate resource management and exception translation. Beyond that they expose callback APIs that allow you to access the store native APIs while still getting exceptions translated and resources managed properly.
any one knows jdbctemplate in spring? Its heavily used in spring. This is the central class in the JDBC core package. This is the class that provides an API. It simplifies the use of JDBC and helps to avoid common errors. It executes core JDBC workflow, leaving application code to provide SQL and extract results. This class executes SQL queries or updates, initiating iteration over ResultSets and catching JDBC exceptions and translating them to the generic, more informative exception hierarchy defined in the org.springframework.dao package. Spring takes this concept and provided templates for noSQL stores you can find MongoTemplate, RedisTemplateOn top of that we'll find opinionated APIs in the shape of template pattern implementations already well known from Spring's JdbcTemplate, JmsTemplate etc. Thus, there is a RedisTemplate, a MongoTemplate and so on. As you probably already know these templates offer helper methods that allow us to execute commonly needed operations like persisting an object with a single statement while automatically taking care of appropriate resource management and exception translation. Beyond that they expose callback APIs that allow you to access the store native APIs while still getting exceptions translated and resources managed properly.
So who is written a GenericDao? On top of that we have Repositories support. So an idea here is that usually you implements some kind of data layer, just having interface and then implementation for different store, like JPA store, mongo store and etc.. and most of the code written is there is a boilerplate.To ease that even more Spring Data provides a repository abstraction on top of the template implementation that will reduce the effort to implement data access objects to a plain interface definition for the most common scenarios like standard CRUD operations as well as executing queries in case the store supports that. This abstraction is actually the most top layer and blends the APIs of the different stores as much as reasonably possible.so we have here an interface based programming model, so you have an interface for the queries you want to trigger and then those methods will be generated without a need to implement this interface. I will show you later on... Уже прошло несколько лет с тех пор, как появился JPA. Работа с Entity Manager увлекательна, но разработчики пишут красивый API, а подробности работы с базой данных скрывают. При этом частая проблема - дублирование имплементации, когда из одного DAO в другой у нас плавно перекочёвывает один и тот же код, в лучшем случае этот код переносится в абстрактный базовый DAO. Spring Data коренным образом решает проблему - при его использовании остаётся только API на уровне интерфейсов, вся имплементация создаётся автоматически с использованием AOP.http://atamanenko.blogspot.com/2012/02/jpa-spring-data-jpa.htmlTo ease that even more Spring Data provides a repository abstraction on top of the template implementation that will reduce the effort to implement data access objects to a plain interface definition for the most common scenarios like standard CRUD operations as well as executing queries in case the store supports that. This abstraction is actually the most top layer and blends the APIs of the different stores as much as reasonably possible. Thus the store specific implementations of it share quite a lot of commonalities.
So who is written a GenericDao? On top of that we have Repositories support. So an idea here is that usually you implements some kind of data layer, just having interface and then implementation for different store, like JPA store, mongo store and etc.. and most of the code written is there is a boilerplate.To ease that even more Spring Data provides a repository abstraction on top of the template implementation that will reduce the effort to implement data access objects to a plain interface definition for the most common scenarios like standard CRUD operations as well as executing queries in case the store supports that. This abstraction is actually the most top layer and blends the APIs of the different stores as much as reasonably possible.so we have here an interface based programming model, so you have an interface for the queries you want to trigger and then those methods will be generated without a need to implement this interface. I will show you later on... Уже прошло несколько лет с тех пор, как появился JPA. Работа с Entity Manager увлекательна, но разработчики пишут красивый API, а подробности работы с базой данных скрывают. При этом частая проблема - дублирование имплементации, когда из одного DAO в другой у нас плавно перекочёвывает один и тот же код, в лучшем случае этот код переносится в абстрактный базовый DAO. Spring Data коренным образом решает проблему - при его использовании остаётся только API на уровне интерфейсов, вся имплементация создаётся автоматически с использованием AOP.http://atamanenko.blogspot.com/2012/02/jpa-spring-data-jpa.htmlTo ease that even more Spring Data provides a repository abstraction on top of the template implementation that will reduce the effort to implement data access objects to a plain interface definition for the most common scenarios like standard CRUD operations as well as executing queries in case the store supports that. This abstraction is actually the most top layer and blends the APIs of the different stores as much as reasonably possible. Thus the store specific implementations of it share quite a lot of commonalities.
So who is written a GenericDao? On top of that we have Repositories support. So an idea here is that usually you implements some kind of data layer, just having interface and then implementation for different store, like JPA store, mongo store and etc.. and most of the code written is there is a boilerplate.To ease that even more Spring Data provides a repository abstraction on top of the template implementation that will reduce the effort to implement data access objects to a plain interface definition for the most common scenarios like standard CRUD operations as well as executing queries in case the store supports that. This abstraction is actually the most top layer and blends the APIs of the different stores as much as reasonably possible.so we have here an interface based programming model, so you have an interface for the queries you want to trigger and then those methods will be generated without a need to implement this interface. I will show you later on... Уже прошло несколько лет с тех пор, как появился JPA. Работа с Entity Manager увлекательна, но разработчики пишут красивый API, а подробности работы с базой данных скрывают. При этом частая проблема - дублирование имплементации, когда из одного DAO в другой у нас плавно перекочёвывает один и тот же код, в лучшем случае этот код переносится в абстрактный базовый DAO. Spring Data коренным образом решает проблему - при его использовании остаётся только API на уровне интерфейсов, вся имплементация создаётся автоматически с использованием AOP.http://atamanenko.blogspot.com/2012/02/jpa-spring-data-jpa.htmlTo ease that even more Spring Data provides a repository abstraction on top of the template implementation that will reduce the effort to implement data access objects to a plain interface definition for the most common scenarios like standard CRUD operations as well as executing queries in case the store supports that. This abstraction is actually the most top layer and blends the APIs of the different stores as much as reasonably possible. Thus the store specific implementations of it share quite a lot of commonalities.
On top of that we have Repositories support. So an idea here is that usually you implements some kind of data layer, just having interface and then implementation for different store, like JPA store, mongo store and etc.. and most of the code written is there is a boilerplate.So who is written a GenericDao? so we have here an interface based programming model, so you have an interface for the queries you want to trigger and then those methods will be generated without a need to implement this interface. I will show you later on... Уже прошло несколько лет с тех пор, как появился JPA. Работа с Entity Manager увлекательна, но разработчики пишут красивый API, а подробности работы с базой данных скрывают. При этом частая проблема - дублирование имплементации, когда из одного DAO в другой у нас плавно перекочёвывает один и тот же код, в лучшем случае этот код переносится в абстрактный базовый DAO. Spring Data коренным образом решает проблему - при его использовании остаётся только API на уровне интерфейсов, вся имплементация создаётся автоматически с использованием AOP.http://atamanenko.blogspot.com/2012/02/jpa-spring-data-jpa.htmlTo ease that even more Spring Data provides a repository abstraction on top of the template implementation that will reduce the effort to implement data access objects to a plain interface definition for the most common scenarios like standard CRUD operations as well as executing queries in case the store supports that. This abstraction is actually the most top layer and blends the APIs of the different stores as much as reasonably possible. Thus the store specific implementations of it share quite a lot of commonalities.
On top of that we have Repositories support. So an idea here is that usually you implements some kind of data layer, just having interface and then implementation for different store, like JPA store, mongo store and etc.. and most of the code written is there is a boilerplate.So who is written a GenericDao? so we have here an interface based programming model, so you have an interface for the queries you want to trigger and then those methods will be generated without a need to implement this interface. I will show you later on... Уже прошло несколько лет с тех пор, как появился JPA. Работа с Entity Manager увлекательна, но разработчики пишут красивый API, а подробности работы с базой данных скрывают. При этом частая проблема - дублирование имплементации, когда из одного DAO в другой у нас плавно перекочёвывает один и тот же код, в лучшем случае этот код переносится в абстрактный базовый DAO. Spring Data коренным образом решает проблему - при его использовании остаётся только API на уровне интерфейсов, вся имплементация создаётся автоматически с использованием AOP.http://atamanenko.blogspot.com/2012/02/jpa-spring-data-jpa.htmlTo ease that even more Spring Data provides a repository abstraction on top of the template implementation that will reduce the effort to implement data access objects to a plain interface definition for the most common scenarios like standard CRUD operations as well as executing queries in case the store supports that. This abstraction is actually the most top layer and blends the APIs of the different stores as much as reasonably possible. Thus the store specific implementations of it share quite a lot of commonalities.