Another Redis Desktop Manager 10.11.2.2 Crack+ [April-2022]
· Program that allows you to control your Redis database: check statistics, create new databases, manage them, add or remove databases and keys
· Detailed node view with links to the Redis file
· Click to add or remove databases and keys
· Click to add or remove IP addresses
· Click to start or stop Redis process
· Double click to edit items
· Actions on items:
- click to list items in a text file for copy or paste
- click to delete item
· Click on 3D node to view keys in the database
· Support sqlite, sqlite3, mongodb, redis, redis full text search
· Redis command line support for ubuntu, centos7, windows
· Redis support for python
· Add and remove keys:
- List or view keys in the app
- Add or edit keys in the app
- Add or edit keys in the text file
- Active keys statistics
· Key statistics:
- Overview of keys in the database:
Total number of keys
Total bytes of keys
Bytes per key
Number of times update
· Per database statistics:
- Overview of database keys and values
· Click on keys to view
· Click on the console for cURL and shell commands
· Back from the menu, click on the refresh button to get available options
· The memory of redis service
· The memory of redis database
· The memory of redis key value
· The memory of redis key
· RAM usage
· CPU usage
· Network usage
· Connections:
- List of existing open connections
- List of open tcp / udp connections
· Count the number of open connections for each ip
· TCP connections
- List of open tcp connections
- List of open udp connections
- List of udp connection
· Memory status:
- Overview of memory status
· Status of the redis server system
· List of connected network hosts
· Memory usage
· CPU usage
· Network usage
· Disk usage
· Memory available
· Memory allocated
· Time spent in GC
· Memory overhead
· Memory pool
· Load average
· Connections / second
· Memory used / second
· CPU used / second
· Network used / second
· Connections / second
· Memory / second
· CPU / second
· Network / second
· Memory available / second
· Memory overhead
Another Redis Desktop Manager 10.11.2.2 Crack
Tired of typing commands on the command-line and then copying the output in to another window?
Made use of names, forgetting the connection name?
Another Redis Desktop Manager comes in to resolve your problems with ease. Being a full-featured software utility you can manage all connections of different types: databases and key-value stores using the intuitive dashboard.
With Another Redis Desktop Manager, you can manage keys and their values, take backups, apply changes, check statistics, reconnect, and check or edit your connection settings.
Hadoop is an open source software framework for distributed storage and processing of large datasets. Hadoop includes a network file system for distributing stored data, as well as job scheduling and distributed data processing.
Hadoop contains a programming interface that is somewhat similar to both MapReduce (a programming model developed by Google) and the Common Intermediate Language (CIL) used by the.NET programming language. Hadoop is implemented in Java, and requires that a computer running it carry a Java virtual machine.
Hadoop’s architecture is modeled after a traditional file-system based computer, with a master daemon in charge of maintaining the cluster, and various services (such as the data mapper and the data reducer) which can be installed in slave machines.
Hadoop provides easy-to-use tools for creating, implementing, and managing MapReduce jobs, and for managing storage and computing resources on the cluster. With Hadoop, tasks performed by both MapReduce and the data nodes can be recorded and repeated.
Hadoop as an open source software framework has found application in a variety of domain areas, for example in managing large data for genomics, the collection of planet-wide geographic data (such as satellite imagery, weather radar, seismic data, and light detection and ranging data), and e-commerce databases.
Apache Kafka is an open source distributed messaging system that was developed to tackle one of the biggest challenges in any system using modern cloud technology: scalability.
The developers of Kafka created a distributed messaging solution that, unlike most other systems, is event-driven and, hence, only as scalable as the events being handled. The APIs used to work with Kafka are similar to those of Apache Kafka, and enable them to be used in a variety of languages.
Kafka uses a flexible publish-subscribe model. For input, it receives data through a customized protocol that puts a timestamp to each event
f0d5c1b395

Related

Items