When working on the computer, you probably use the same programs each day and work with files in the same folders. Here are the best productivity hacks that the Stream Deck has to offer: I have lots of experience playing around with the Stream Deck and I have discovered a few tricks that will make you more efficient while you are working or just playing around on the computer. You can easily collapse or turn off the sections that you don’t want to use, so don’t get overwhelmed. When you first open the Stream Deck software, you will notice there are a ton of custom actions. In fact, the Elgato Stream Deck made our list as one of the Best Streaming Accessories for 2020.
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Whether you are a graphic designer, video editor, software engineer, or a general freelancer, you will undoubtedly benefit from having a Stream Deck. If you feel like going the extra mile, there is a giant 32 key version called the Stream Deck XL which features a magnetic stand and a removable USB-C cable.Įlgato originally created the Stream Deck to make video game streaming easier, but after many updates and added functionality, it is widely being used as a productivity tool for everyday work. If you are on a budget, there is a Stream Deck Mini which has only 6 keys and can easily fit on any desk or surface. The buttons can also be customized to display any image or icon so you can easily identify which action each button performs. Using Elgato’s software, the keys can be mapped to custom controls, commands, and much more. The Stream Deck is a USB device with 15 keys that each have a small LCD screen.
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In this article, I’ll teach you how to use the Elgato Stream Deck to hack your productivity. Don’t manually define partitions using more than two columns since writing the boundary predicates require much more complex logic.Do you have trouble staying productive while you are working? Do you struggle to remember helpful keyboard shortcuts? Are you constantly performing repetitive tasks and typing the same things over and over? With the Elgato Stream Deck, your life can become a whole lot easier. When defining custom partitions, remember to consider NULL when the partition columns are Nullable. Jdbc(url:String,table:String,predicates:Array.) accepts an array of WHERE conditions that can be used to define custom partitions: this is useful for partitioning on non-numeric columns or for dealing with skew. This work well if your database table has an indexed numeric column with fairly evenly-distributed values, such as an auto-incrementing primary key it works somewhat less well if the numeric column is extremely skewed, leading to imbalanced tasks.
Jdbc(url:String,table:String,partitionColumn:String,lowerBound:Long,upperBound:Long,numPartitions:Int.)takes the name of a numeric, date, or timestamp column ( partitionColumn), two range endpoints ( lowerBound, upperBound) and a target numPartitions and generates Spark tasks by evenly splitting the specified range into numPartitions tasks. You can use two DataFrameReader APIs to specify partitioning: See the Spark SQL programming guide for other parameters, such as fetchsize, that can help with performance. Each task is spread across the executors, which can increase the parallelism of the reads and writes through the JDBC interface. In the Spark UI, you can see that the number of partitions dictate the number of tasks that are launched.
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