167 posts
Last time we looked at the Thread class and the Runnable interface, but that pairing has one problem: no return value. If we want the thread to hand a value back, we need FutureTask and Callable, which is what this post covers.
Last time we talked broadly about why we need multiple threads. Now that we want to study concurrency, let's create threads ourselves and dig into its mysteries.
Hive's atomic data types support implicit conversion, similar to Java's type conversion. If an expression uses INT, for example, a TINYINT is automatically converted to INT — but Hive never converts in the reverse direction.
What's the relationship between high concurrency and multithreading? I never create threads in my code, so why does everyone start talking about multithreading the moment the subject comes up? My opening post digs into why we should learn multithreading, and how high concurrency turns into multithreading.
Last time we learned what Hive is. This post walks you through installing and deploying Hive so you can try this legendary data warehouse yourself.
Having finished the Hadoop beginner series, we're finally getting to the real data warehouse work. Let's start by understanding what Hive is in the Hadoop ecosystem.
Three days ago, two malicious commits were pushed into the php-src repository maintained by the PHP team on its git.php.net server. Both commits faked signatures — his own, and that of PHP creator Rasmus Lerdorf.
The first three ZooKeeper tutorials left you able to use it. This post goes a step further and gives you a general idea of how ZooKeeper actually works.
Last time we could already drive ZooKeeper from code and learned about registering watchers. Time to try it out: this post walks through a simple hands-on example that watches a node for changes.
Last post got ZooKeeper installed. The command line works, but most of the time you operate ZooKeeper through API calls, so this post covers the basic beginner-level operations.
