We all have the need to serialize/deserialize objects (either through the "wire" or to file). In this podcast we go and analyze what exactly happens when we create an ObjectOutputStream and write to it, and more importantly what pitfalls are there to avoid (Out ot memory errors, stale object updates, Not Serializable Exceptions, and toenail fungus!). If you ever considered using ObjectOutput/InputStream, or are actively using in your current projects, take a listen!
https://github.com/eishay/jvm-serializers/wiki/ (Serialization performance comparison for Java, pick one!)
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Episode 18. Ahh, the perils of Serialization and Deserialization in Java

This podcast talks about how to program in Java; not your tipical system.out.println("Hello world"), but more like real issues, such as O/R setups, threading, getting certain components on the screen or troubleshooting tips and tricks in general. The format is as a podcast so that you can subscribe to it, and then take it with you and listen to it on your way to work (or on your way home), and learn a little bit more (or reinforce what you knew) from it.

Technology

Tech News

Podcasting

Gadgets

Software How-To

So we continue to have guests in our show to talk to us about interesting things... This time is about Apache Tika. This is an incredible tool to do search file processing and metadata extraction. Think about that you have tons of unstructured files, like emails, or documents, and you want to extract, index and then search theses. This is Tika's purpose. And who best to walk us through how it does its magic that its Project Management Committee (PMC) Chair, Tim Allison! So take a listen as we go deeper on ingesting tons of content (which is fundamental for things like training LLMs). http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode  Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/ Apache Tika * https://tika.apache.org/ OpenSearch Project and OpenSearch Neural Plugin Tutorials * https://opensearch.org/ * https://opensearch.org/docs/latest/search-plugins/neural-search/  * https://opster.com/guides/opensearch/opensearch-machine-learning/how-to-set-up-vector-search-in-opensearch/   * https://opster.com/guides/opensearch/opensearch-machine-learning/opensearch-hybrid-search/  * https://sease.io/2024/01/opensearch-knn-plugin-tutorial.html * https://sease.io/2024/04/opensearch-neural-search-tutorial-hybrid-search.html Selected Advanced File Processing toolkits/services * https://unstructured.io/ * https://aws.amazon.com/textract/ * https://azure.microsoft.com/en-us/products/ai-services/ai-document-intelligence Selected Hybrid Search/RAG toolkits (there are _MANY_ others!) * Haystack: https://haystack.deepset.ai/ * LangChain: https://www.langchain.com/ * LangStream: https://langstream.ai/ Search/Relevance Conferences * https://haystackconf.com/ * https://2024.berlinbuzzwords.de/ * https://mices.co/ Tim's personal project * JavaFX (ahem) tika-config writer UI: https://github.com/tballison/tika-gui-v2  Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse

Episode 104. It's all about Apache Tika, the project that lets you index EVERYTHING.

We have a great time talking to Matt Topol from Voltron Data on one of his Apache Software Foundation projects called Apache Arrow. It's both a spec and implementation of a columnar data format that is not only efficient, but cross-language compatible. We walk through the scenarios that it covers and how is becoming more and more pivotal for things like ML and LLMs. So come listen to this JPH episode on one of the best and free ways to distribute data and integrate services working on top of that data! http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode  Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/  - Apache Arrow Project (https://arrow.apache.org/)  - Java implementation (https://arrow.apache.org/docs/java/index.html)  - In-Memory Analytics with Apache Arrow (https://www.oreilly.com/library/view/in-memory-analytics-with/9781801071031/)   - Matt Topol X (Twitter!) Account (https://twitter.com/zeroshade)  -  Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse

Episode 103. Let's share data cross-language with Apache Arrow! (among other things)

Ok, so it's an incredible time to be in the Java Ecosystem, and one of the biggest frameworks out there just dropped their three-point-oh version! That's right! So Spring Boot is not officially 3.0, and it has as a Baseline Java 17! (oohh!!). So we brought in the big guns to talk about what does it mean to Upgrade to Spring Boot 3, and what are the new cool toys we can expect from that upgrade!  In all, an amazing interview full of great things that are available NOW (so whatcha waiting for! Upgrade!) http://www.javapubhouse.com/datadog We thank DataDogHQ for sponsoring this podcast episode  Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/  - Dan Vega's own What's new in Spring Boot 3 (https://www.danvega.dev/newsletter/whats-new-spring-boot-3/)  - Official Spring Framework 6 Wiki (https://github.com/spring-projects/spring-framework/wiki/What's-New-in-Spring-Framework-6.x)   - Spring Boot 3, and Spring Framework 6, What's new? (https://www.baeldung.com/spring-boot-3-spring-6-new)  - Spring Boot 3 goes GA (https://spring.io/blog/2022/11/24/spring-boot-3-0-goes-ga)  - Preparing for Spring Boot 3 (https://spring.io/blog/2022/05/24/preparing-for-spring-boot-3-0)   -  Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse

Episode 102. Oh my... Spring Boot 3 is out! An interview with Dan Vega from the Pivotal Team!

Whew! So we took a big break over summer (like Bob said, we were just swamped with work.. oof), but we are BACK! and like always we are ready to explore even deeper Java topics for the professional developer. This time we set our sights in Apache Kafka, one of the (if not THE) dominant distributed messaging framework / broker. If you have been integrating webservices, you might have been running into message brokers (and applying Enterprise Integration Patterns), well if so, you most likely have run into Kafka.  We dive into "What does Kafka Solve", into what it is (and isn't), and why you should use it (or not use it), and how it differs from traditionalling Messaging systems. In all, this is another episode of "Cloud stuff", and, like you know, that's where everything interesting is at! So have a listen!  http://www.javapubhouse.com/datadog  We thank DataDogHQ for sponsoring this podcast episode  Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/ Apache Kafka https://kafka.apache.org/ Kafka Quick Start  https://developer.confluent.io/quickstart/kafka-on-confluent-cloud/ What IS Apache Kafka https://developer.confluent.io/what-is-apache-kafka/ Apache Kafka Quickstart (With Tim Berglund, Hi!!!) https://kafka.apache.org/quickstart  Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse  

Episode 101. Allright, let's talk about Kafka

Yeah! so we have been working with the cloud for a while, terms like K8s, EC2, Route53, BlobData, CLI has been swinged around... and is a little mysterious, and sometimes looks like a black box where you just click buttons, add things, type commands, until it finally something good happens. But if something bad happens, we tend not to have the slightest idea on why! Never fear, on this episode of PubHouse we start from the very beginning on describing (And dismantling) what the "Cloud" really is... Starting on how we got there, what are the different "components" of most clouds, and how to reason about them. This way, the next time something unpredictable happens, you will know exactly where to start troubleshooting and how to navigate this space! This is the first episode of a series (probably a series of 2) on Cloud technologies. So if you never been exposed to the cloud and you're curious, or even if you've been working on it but everything sounds mysterious, then dive in! http://www.javapubhouse.com/datadog  We thank DataDogHQ for sponsoring this podcast episode Don't forget to SUBSCRIBE to our cool NewsCast OffHeap! http://www.javaoffheap.com/ Intro to AWS  https://docs.aws.amazon.com/whitepapers/latest/aws-overview/introduction.html What is Elastic Load Balancing https://docs.aws.amazon.com/elasticloadbalancing/latest/userguide/what-is-load-balancing.html What is Amazon Route 53 https://docs.aws.amazon.com/Route53/latest/DeveloperGuide/Welcome.html EC2 vs ECS vs Lambda https://www.cloudzero.com/blog/ecs-vs-ec2 Intro to Azure Fundamentals https://docs.microsoft.com/en-us/learn/modules/intro-to-azure-fundamentals/ Azure Containter Registry https://azure.microsoft.com/en-us/services/container-registry/#features Azure Compute https://azure.microsoft.com/en-us/services/virtual-machines/#overview Do you like the episodes? Want more? Help us out! Buy us a beer! https://www.javapubhouse.com/beer And Follow us!  https://www.twitter.com/javapubhouse  

Episode 18. Ahh, the perils of Serialization and Deserialization in Java

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