A new version of Liberica JRE Portable 21 LTS has been released by PortableApps.com. Liberica JRE Portable allows you to carry a full-featured Java® runtime environment (JRE) on your PortableApps.com-enabled device all without any Java runtime on the local PC. It's packaged in PortableApps.com Format for easy use from any portable device and integration with the PortableApps.com Platform. It's open source for personal and business use. _Update automatically or install from the portable app store in the PortableApps.com Platform._ _Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners._

Java Download stellt die aktuelle Java Runtime Environment von Oracle bereit, um Java-Anwendungen au

The Linux kernel's binfmt_misc functionality allows non-native/custom files to ne run directly such as for Windows EXE files to be handled by Wine or JAR files to be handled by the Java runtime. For the upcoming Linux 7.3 merge window, the miscellaneous binary formats support is being extended so a binary type can be matched programmatically and the interpreter determined on a per-exec basis. BPF programs can also then be attached to dynamically choosing an execution environment on a per-binary basis...

The Linux kernel's binfmt_misc functionality allows non-native/custom files to ne run directly such as for Windows EXE files to be handled by Wine or JAR files to be handled by the Java runtime. For the upcoming Linux 7.3 merge window, the miscellaneous binary formats support is being extended so a binary type can be matched programmatically and the interpreter determined on a per-exec basis. BPF programs can also then be attached to dynamically choosing an execution environment on a per-binary basis...

Unspecified vulnerability in the Java Runtime Environment (JRE) component in Oracle Java SE 7 Update 2 and earlier, 6 Update 30 and earlier, and 5.0 Update 33 and earlier allows remote attackers to affect confidentiality, integrity, and …

Multiple vulnerabilities in the Java Runtime Environment (JRE) component in Oracle Java SE 7 Update 6 and earlier allow remote attackers to execute arbitrary code via a crafted applet that bypasses SecurityManager restrictions by (1) usi…

Unspecified vulnerability in the Java Runtime Environment (JRE) component in Oracle Java SE 7 update 4 and earlier, 6 update 32 and earlier, 5 update 35 and earlier, and 1.4.2_37 and earlier allows remote attackers to affect confidential…

## S1. Update the System Before installing Hadoop, update your system packages. sudo apt update sudo apt upgrade -y ## S2. Install and Configure Java 21 Apache Hadoop is written in Java and requires a compatible Java Runtime Environment (JRE) and Java Development Kit (JDK). This guide uses **OpenJDK 21 (LTS)**. ## Java Compatibility Installed Java Version | Action ---|--- Java 21 | Continue with the installation Java 17 | May work with some Hadoop versions, but this guide uses Java 21 Java 22–25 | Install Java 21 and switch to it Java Not Installed | Install OpenJDK 21 ### S2.1 Check if Java is Installed java -version javac -version #### If Java is NOT Installed Install OpenJDK 21. sudo apt update sudo apt install openjdk-21-jdk -y Verify the installation. java -version javac -version #### If Java is Already Installed Check the installed version. java -version javac -version Compare the output with the compatibility table above. If Java 21 is already active, continue to the next step. Otherwise, switch to Java 21. ### S2.2 List All Installed Java Versions update-java-alternatives -l Example: java-1.17.0-openjdk-amd64 java-1.21.0-openjdk-amd64 ### S2.3 Switch to Java 21 sudo update-alternatives --config java sudo update-alternatives --config javac Select the option corresponding to **Java 21**. ### S2.4 Verify the Active Java Version java -version javac -version Both commands should display **Java 21**. ### S2.5 Find the Correct JAVA_HOME Different Linux distributions may install Java in different directories. Instead of copying someone else's path, determine it automatically. readlink -f $(which java) Example: /usr/lib/jvm/java-21-openjdk-amd64/bin/java Therefore, JAVA_HOME=/usr/lib/jvm/java-21-openjdk-amd64 > **Note:** Never blindly copy the `JAVA_HOME` path from a tutorial. Always determine it using the command above. ## S3. Download Apache Hadoop 3.4.2 Move to the directory where you want to download Hadoop. cd ~/Downloads Download Hadoop from the official Apache Archive. wget https://archive.apache.org/dist/hadoop/common/hadoop-3.4.2/hadoop-3.4.2.tar.gz Verify the download. ls -lh hadoop-3.4.2.tar.gz Expected output: -rw-r--r-- 1 user user 734M hadoop-3.4.2.tar.gz ## S4. Extract and Install Hadoop After downloading the Hadoop archive, the next step is to extract it and install Hadoop on your system. In this guide, Hadoop will be installed under **`/opt/hadoop`** , which is the standard location for optional third-party software on Linux. ### S4.1 Extract the Archive Move to the directory where the archive was downloaded. cd ~/Downloads Extract the archive. tar -xvzf hadoop-3.4.2.tar.gz This will create a directory named: hadoop-3.4.2 Verify the extraction. ls Expected output: hadoop-3.4.2 hadoop-3.4.2.tar.gz ### S4.2 Move Hadoop to /opt Move the extracted directory to `/opt`. sudo mv hadoop-3.4.2 /opt/hadoop ### S4.3 Verify the Installation Directory Check that Hadoop has been moved successfully. ls /opt Expected output: hadoop View the contents of the Hadoop directory. ls /opt/hadoop Expected output: bin etc include lib libexec licenses sbin share NOTICE.txt README.txt ... ### S4.4 Change Ownership By default, the Hadoop directory is owned by the root user because it was moved using `sudo`. Change the ownership so your user can modify the configuration files without requiring root privileges every time. sudo chown -R $USER:$USER /opt/hadoop Verify the ownership. ls -ld /opt/hadoop Example output: drwxr-xr-x <username> <username> ... ### S4.5 Verify the Hadoop Version Run the Hadoop executable directly. /opt/hadoop/bin/hadoop version Expected output: Hadoop 3.4.2 Source code repository ... Compiled by ... At this point, Hadoop has been successfully installed on the system. However, it cannot yet be executed from any directory because its binaries have not been added to the system's PATH. > **Note:** We are intentionally using the full path (`/opt/hadoop/bin/hadoop`) for now. In the next section, we will configure environment variables so that the `hadoop`, `hdfs`, and `yarn` commands can be run from anywhere in the terminal. ## S5. Configure Environment Variables After installing Hadoop, we need to configure environment variables. These variables tell the operating system where Hadoop and Java are installed, allowing Hadoop commands to be executed from any directory. The main environment variables are: Variable | Purpose ---|--- `JAVA_HOME` | Points to the Java installation directory `HADOOP_HOME` | Points to the Hadoop installation directory `HADOOP_CONF_DIR` | Specifies the Hadoop configuration directory `PATH` | Allows Hadoop commands to be executed from anywhere ### S5.1 Check Your Default Shell Before editing your shell configuration, determine which shell you are using. echo $SHELL Possible outputs: /bin/bash or /bin/zsh ### S5.2 Open the Shell Configuration File ### If you are using Bash nano ~/.bashrc ### If you are using Zsh nano ~/.zshrc ### S5.3 Add the Hadoop Environment Variables Append the following lines to the end of the file. # Java export JAVA_HOME=$(dirname $(dirname $(readlink -f $(which java)))) # Hadoop export HADOOP_HOME=/opt/hadoop export HADOOP_CONF_DIR=$HADOOP_HOME/etc/hadoop # Hadoop Components export HADOOP_COMMON_HOME=$HADOOP_HOME export HADOOP_HDFS_HOME=$HADOOP_HOME export HADOOP_MAPRED_HOME=$HADOOP_HOME export YARN_HOME=$HADOOP_HOME # Native Libraries export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native # PATH export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin ### Why use `$(dirname $(dirname $(readlink -f $(which java))))`? Instead of hardcoding the Java installation path, this command automatically determines the correct `JAVA_HOME` directory. This makes the guide more portable across different Linux distributions and Java installation methods. ### S5.4 Save the File For Nano: * Press **Ctrl + O** * Press **Enter** * Press **Ctrl + X** ### S5.5 Reload the Configuration ### Bash source ~/.bashrc ### Zsh source ~/.zshrc ### S5.6 Verify the Environment Variables Check that Hadoop is configured correctly. echo $JAVA_HOME Example: /usr/lib/jvm/java-21-openjdk-amd64 Check the Hadoop installation directory. echo $HADOOP_HOME Expected output: /opt/hadoop Check the configuration directory. echo $HADOOP_CONF_DIR Expected output: /opt/hadoop/etc/hadoop ### S5.7 Verify Hadoop Commands You should now be able to run Hadoop commands from any directory. Check the Hadoop version. hadoop version Check the HDFS version. hdfs version Check the YARN version. yarn version Each command should report **Hadoop 3.4.2**. > **Note:** If any of these commands return `command not found`, ensure that the shell configuration file has been reloaded using the `source` command or open a new terminal session. ## S6. Configure Passwordless SSH Apache Hadoop uses SSH to start and stop its daemons. Even in a single-node cluster, passwordless SSH is required for Hadoop scripts such as `start-dfs.sh` and `start-yarn.sh`. ### S6.1 Check if OpenSSH is Installed Run the following command: ssh -V If OpenSSH is installed, you will see output similar to: OpenSSH_10.x If the command is not found, install the OpenSSH server. sudo apt update sudo apt install openssh-server -y ### S6.2 Start and Enable the SSH Service Start the SSH service. sudo systemctl start ssh Enable it to start automatically on boot. sudo systemctl enable ssh Check the service status. sudo systemctl status ssh The status should show **active (running)**. Exit the status screen by pressing **Q**. ### S6.3 Generate an SSH Key Pair If you do not already have an SSH key, generate one. ssh-keygen -t rsa -b 4096 When prompted for the file location, simply press **Enter** to accept the default location. When prompted for a passphrase, press **Enter** twice to leave it empty. Example: Enter file in which to save the key: /home/<username>/.ssh/id_rsa ### S6.4 Enable Passwordless SSH Append the public key to the authorized keys file. cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys Set the correct permissions. chmod 700 ~/.ssh chmod 600 ~/.ssh/authorized_keys ### S6.5 Test the SSH Connection Run: ssh localhost The first time you connect, you may see: Are you sure you want to continue connecting (yes/no)? Type: yes If everything is configured correctly, you will be logged into your own machine without entering a password. Exit the SSH session. exit ### Why is Passwordless SSH Required? Hadoop's management scripts use SSH to launch and stop services such as the NameNode, DataNode, ResourceManager, and NodeManager. Without passwordless SSH, these scripts will repeatedly prompt for a password, making automated startup impossible. ## S7. Create Hadoop Data Directories Hadoop requires a few directories to store its metadata and temporary files. These directories are referenced by the Hadoop configuration files. Create the required directories by running the following commands: mkdir -p ~/hadoopdata/namenode mkdir -p ~/hadoopdata/datanode mkdir -p ~/hadooptmp You can verify that the directories were created successfully using: tree -L 2 ~ If the `tree` command is not installed, install it using: sudo apt install tree -y Expected output: /home/<username> ├── hadoopdata │ ├── datanode │ └── namenode └── hadooptmp > **Note:** The directory names must match the paths specified in the Hadoop configuration files (`core-site.xml` and `hdfs-site.xml`). If you changed those paths, create the directories accordingly. ## S8. Install the Hadoop Configuration Files Instead of manually editing multiple Hadoop configuration files, use the installation script provided in the GitHub repository. The script downloads and installs all the required configuration files automatically. Download the installation script. wget https://raw.githubusercontent.com/itsadityapidurkar/hadoop-installation-guide/main/linux/install-configs.sh Make the script executable. chmod +x install-configs.sh Run the script. ./install-configs.sh The script downloads and installs the following configuration files: * `core-site.xml` * `hdfs-site.xml` * `mapred-site.xml` * `yarn-site.xml` * `workers` These files are automatically copied to: /opt/hadoop/etc/hadoop If the script completes successfully, you should see: ======================================== Apache Hadoop Configuration Installer ======================================== [+] Downloading configuration files... [✓] Download complete. [+] Installing configuration files... [✓] Configuration files installed successfully! Installed to: /opt/hadoop/etc/hadoop > **Note:** The provided configuration files are intended for a **Single Node Hadoop 3.4.2** installation. If you modified the directory paths while following this guide, update the configuration files accordingly before installing them. ## S9. Configure `hadoop-env.sh` The `hadoop-env.sh` file is used to configure environment variables required by Hadoop. The only change required for this guide is to set the `JAVA_HOME` variable. Open the file using a text editor. nano /opt/hadoop/etc/hadoop/hadoop-env.sh Search for the line containing: export JAVA_HOME= or # export JAVA_HOME= Replace it with: export JAVA_HOME=$(dirname $(dirname $(readlink -f $(which java)))) Save the file and exit. For Nano: * Press **Ctrl + O** * Press **Enter** to save the file. * Press **Ctrl + X** to exit. You can verify that the `JAVA_HOME` path is detected correctly by running: echo $(dirname $(dirname $(readlink -f $(which java)))) Example output: /usr/lib/jvm/java-21-openjdk-amd64 > **Note:** This command automatically detects the Java installation directory, making the configuration portable across different Linux distributions and Java installation paths. ## S10. Format the NameNode Before starting Hadoop for the first time, the NameNode must be formatted. This initializes the Hadoop Distributed File System (HDFS) and creates the required metadata. Run the following command: hdfs namenode -format During the formatting process, you may be prompted with the following message if the NameNode directory already contains data: Re-format filesystem in Storage Directory root=... ? (Y or N) Type: Y and press **Enter**. If the formatting is successful, the last few lines of the output should look similar to: ... INFO common.Storage: Storage directory ... has been successfully formatted. INFO namenode.FSImageFormatProtobuf: Saving image file ... INFO namenode.NameNode: SHUTDOWN_MSG: > **Important:** Formatting the NameNode permanently removes all existing HDFS metadata and data stored in the configured NameNode and DataNode directories. This command should only be executed during the initial setup or when you intentionally want to reset the Hadoop cluster. Do **not** run this command every time you start Hadoop. ## S11. Start HDFS Now that the NameNode has been formatted, you can start the Hadoop Distributed File System (HDFS). Run the following command: start-dfs.sh If HDFS starts successfully, you should see output similar to: Starting namenodes on [localhost] Starting datanodes Starting secondary namenodes [<hostname>] To verify that all HDFS daemons are running, execute: jps Expected output: NameNode DataNode SecondaryNameNode Jps > **Note:** The order of the processes may vary depending on your system. You can also verify that the NameNode is running by opening the following URL in your web browser: http://localhost:9870 If HDFS has started successfully, the NameNode web interface will be displayed, showing information about the cluster, storage usage, live DataNodes, and the HDFS filesystem. ## S12. Start YARN After starting HDFS, the next step is to start YARN (Yet Another Resource Negotiator), which is responsible for resource management and job scheduling in the Hadoop cluster. Run the following command: start-yarn.sh If YARN starts successfully, you should see output similar to: Starting resourcemanager Starting nodemanagers To verify that the YARN daemons are running, execute: jps Expected output: NameNode DataNode SecondaryNameNode ResourceManager NodeManager Jps > **Note:** The order of the processes may vary depending on your system. You can also verify that YARN is running by opening the following URL in your web browser: http://localhost:8088 If YARN has started successfully, the ResourceManager web interface will open, displaying information about the cluster, available resources, running applications, and node status. At this point, your Hadoop Single Node Cluster is up and running. ## S13. Verify the Hadoop Installation After starting both HDFS and YARN, verify that all Hadoop services are running correctly. Check the running Hadoop daemons. jps Expected output: NameNode DataNode SecondaryNameNode ResourceManager NodeManager Jps View the HDFS cluster report. hdfs dfsadmin -report If the cluster is running correctly, the report will display information about the configured capacity, remaining storage, live DataNodes, and other cluster details. Next, open the NameNode Web UI in your browser. http://localhost:9870 The NameNode dashboard should display information such as: * Cluster Summary * Live DataNodes * Storage Information * HDFS Overview Then open the ResourceManager Web UI. http://localhost:8088 The ResourceManager dashboard should display: * Cluster Metrics * Node Status * Running Applications * Available Resources If all the above commands and web interfaces are accessible, your Hadoop Single Node Cluster has been installed and configured successfully. ### Hadoop Web UI Port Quick-Reference Service | Web UI URL | Default Port | Description ---|---|---|--- **HDFS NameNode** | `http://localhost:9870` | 9870 | File system status, capacity, browser directories **YARN ResourceManager** | `http://localhost:8088` | 8088 | Job executions, node resource allocation **HDFS DataNode** | `http://localhost:9864` | 9864 | Individual DataNode status & blocks ## S14. Shut Down the Hadoop Cluster To stop the Hadoop daemons and release system resources safely, stop the YARN resource manager and HDFS services in order. Run the following commands: stop-yarn.sh stop-dfs.sh To verify that all Hadoop services have been stopped successfully, run: jps Expected output: Jps Only the `Jps` process itself should be running, confirming that HDFS and YARN have successfully shut down.

The global Java development ecosystem experienced significant structural changes this week following the introduction of a new OpenJDK enhancement draft alongside warnings from cybersecurity researchers regarding a highly adaptive, cross-platform malware strain built on the language's runtime environment. @tonyshan #techinnovation https://bit.ly/tonyshan https://bit.ly/tonyshan_X

The global Java development ecosystem experienced significant structural changes this week following the introduction of a new OpenJDK enhancement draft alongside warnings from cybersecurity researchers regarding a highly adaptive, cross-platform malware strain built on the language's runtime environment.

Serverless and edge runtimes are great until your app needs a normal TCP database connection. ZedGi works with: * **TypeScript / JavaScript SDK** : Cloudflare Workers, Vercel Edge, Deno, Bun, Node.js, AWS Lambda, and any runtime with `fetch`. * **Python SDK** : FastAPI, Flask, Django, scripts, background jobs, AWS Lambda, and other Python services. * **Raw HTTP API** : curl, Go, PHP, Ruby, Java, Rust, no-code tools, internal platforms, and any environment that can send signed HTTPS requests. Cloudflare Workers, Vercel Edge, Deno Deploy, and many other HTTP-first runtimes do not let you open raw TCP sockets directly. That creates an awkward choice: * Move to a provider-specific serverless database. * Add a custom backend just to proxy database calls. * Expose database ports and manage networking yourself. * Give up on running that part of the app at the edge. ZedGi is built for the other path: keep your own Redis, Postgres, or MySQL database, but call it from any HTTP runtime. ## What is ZedGi? ZedGi is a TCP-to-HTTP proxy for Redis, Postgres, and MySQL. You register a database service once, then your app sends signed HTTPS requests to your ZedGi endpoint. ZedGi authenticates the request, routes it to a bridge node, opens the real TCP connection, runs the command or query, and returns JSON. The basic flow looks like this: Your app -> HTTPS request -> ZedGi gateway -> bridge proxy -> Redis / Postgres / MySQL That means code running in an edge or serverless runtime can still talk to traditional TCP databases without managing VPNs, public database ports, or long-lived connection pools in your function. ## Why developers use it ### Use the database you already have ZedGi is not a hosted Redis-only, Postgres-only, or MySQL-only product. It is designed for teams that already have a database somewhere and want to make it reachable from HTTP-only runtimes. Supported services: * Redis * Postgres * MySQL * Custom TCP services (on request) ### Works from any HTTP runtime If your runtime can make an HTTPS request, it can call ZedGi. That includes: * Cloudflare Workers * Vercel Edge Functions * AWS Lambda * Deno * Bun * Node.js * Any environment with `fetch` ### Credentials are not stored in ZedGi Database credentials are supplied at call time by your application. The client encrypts the credential payload before it leaves your app. ZedGi stores service metadata like host, port, service type, and optional caller IP allowlist, but not your plaintext database password. ## Example: Redis from an edge runtime Install the client: npm install @zedgi/zedgi-client Then call Redis over HTTPS: import { createZedgiClient } from "@zedgi/zedgi-client"; const zedgi = createZedgiClient({ url: "https://your-subdomain.zedgi.app", key: process.env.ZEDGI_KEY!, }); const redis = zedgi.redis({ credential: { password: process.env.REDIS_PASSWORD, db: 0, }, }); await redis.set("edge:hello", "world"); const value = await redis.get("edge:hello"); console.log(value); // "world" The same pattern works for Postgres and MySQL. ## Example: Postgres query const pg = zedgi.postgres({ credential: { user: process.env.PG_USER!, password: process.env.PG_PASSWORD!, database: process.env.PG_DATABASE!, ssl: true, }, }); const { rows } = await pg.query( "select id, email from users where id = $1", [userId] ); ## Example: MySQL query const mysql = zedgi.mysql({ credential: { user: process.env.MYSQL_USER!, password: process.env.MYSQL_PASSWORD!, database: process.env.MYSQL_DATABASE!, }, }); const [rows] = await mysql.query( "select id, email from users where id = ?", [userId] ); ## What about security? ZedGi uses a few layers: * API keys identify the caller. * Requests are signed to prevent tampering and replay. * Database credentials are encrypted client-side. * Optional caller IP allowlisting can restrict which source IP may use a service. * The proxy bridge only decrypts credentials transiently to open the TCP connection. The goal is simple: your edge app can call your database, but ZedGi does not become a place where plaintext database passwords sit around. ## When ZedGi is useful ZedGi is a good fit when: * You want Cloudflare Workers or edge functions to talk to your existing database. * You do not want to migrate to a vendor-specific serverless database. * You need Redis, Postgres, and MySQL behind one HTTPS access layer. * You have a custom TCP service you want to expose through the same HTTPS proxy model. * You want a dashboard for API keys, services, usage, and billing. * You need to keep database ports private. It is especially useful for internal tools, SaaS dashboards, lightweight APIs, queues, webhook workers, and jobs that need database access from serverless environments. ## Try it Create an account, register a service, generate an API key, and make your first call: 👉 https://zedgi.app Docs: 👉 https://zedgi.app/docs/ If you have been avoiding edge/serverless because your database still speaks TCP, ZedGi gives you a practical bridge: keep the database, call it over HTTPS.

A free JVM vulnerability risk assessment gives organizations visibility into their entire Java stack – before AI attackers find the vulnerabilities. Azul addresses the blind spot in Java runtime security that autonomous AI can now exploit. The old hurdle of expertise for attacks is being bypassed by AI-powered attacks. The new free JVM vulnerability risk assessment addresses hidden security risks in the Java environment that autonomous AI exploit tools can increasingly exploit. With the mean time to exploit (MTTE) reduced from months to days or hours, unmanaged Java environments have become an urgent security threat for organizations. The Azul assessment… Read more

I’ve cleaned all libjglios folders and run it again with the exact same result. I’m using 0.0-SNAPSHOT for all dependencies, the plugin and org.ngengine:libjglios-core-ios In case it helps, the jvm I have installed is $ java -version openjdk version "21.0.11" 2026-04-21 LTS OpenJDK Runtime Environment Temurin-21.0.11+10 (build 21.0.11+10-LTS) OpenJDK 64-Bit Server VM Temurin-21.0.11+10 (build 21.0.11+10-LTS, mixed mode)

Hazelcast has officially released Hazelcast Platform 5.7.0, an update that introduces production-grade support for the Java 25 runtime environment. The release, launched on May 28, 2026, aims to strengthen the operational foundations of enterprise systems that rely on real-time processing.

A new version of OpenJDK JRE Portable has been released by PortableApps.com. OpenJDK JRE Portable allows you to carry a full-featured Java® runtime environment (JRE) on your PortableApps.com-enabled device all without any Java runtime on the local PC. It's packaged in PortableApps.com Format for easy use from any portable device and integration with the PortableApps.com Platform. It's open source for personal and business use. _Update automatically or install from the portable app store in the PortableApps.com Platform._ _Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners._