redis-processing | use Redis in Processing | Key Value Database library

 by   nok Java Version: Current License: Non-SPDX

kandi X-RAY | redis-processing Summary

kandi X-RAY | redis-processing Summary

redis-processing is a Java library typically used in Database, Key Value Database applications. redis-processing has low support. However redis-processing has 6 bugs, it has 4 vulnerabilities, it build file is not available and it has a Non-SPDX License. You can download it from GitHub.

Introduction to Redis: Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
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            kandi-support Support

              redis-processing has a low active ecosystem.
              It has 19 star(s) with 2 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              redis-processing has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of redis-processing is current.

            kandi-Quality Quality

              redis-processing has 6 bugs (0 blocker, 0 critical, 2 major, 4 minor) and 265 code smells.

            kandi-Security Security

              redis-processing has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              redis-processing code analysis shows 4 unresolved vulnerabilities (0 blocker, 0 critical, 0 major, 4 minor).
              There are 2 security hotspots that need review.

            kandi-License License

              redis-processing has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              redis-processing releases are not available. You will need to build from source code and install.
              redis-processing has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions, examples and code snippets are available.
              redis-processing saves you 5973 person hours of effort in developing the same functionality from scratch.
              It has 12465 lines of code, 2874 functions and 84 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed redis-processing and discovered the below as its top functions. This is intended to give you an instant insight into redis-processing implemented functionality, and help decide if they suit your requirements.
            • Initialize Redis client from URI
            • Get the DB index from the given URI
            • Connect to the data source
            • Compares the host and port
            • Writes a UTF - 8 string
            • Execute the current command
            • Initializes a slave of Sentinels
            • Pop a value from a list
            • Validates the provided Jedis object
            • Writes ascii characters
            • Synchronize the pipeline with all responses
            • Closes the connection
            • Initializes the pool with the given master
            • Compares this tuple to another
            • Execute the transaction
            • Create a Jedis object
            • Initialize the shards
            • Set sentinel
            • Returns the number of bytes required to encode the given string
            • Initialize Redis server
            • Executes and returns response
            • Calculates the hash code
            Get all kandi verified functions for this library.

            redis-processing Key Features

            No Key Features are available at this moment for redis-processing.

            redis-processing Examples and Code Snippets

            No Code Snippets are available at this moment for redis-processing.

            Community Discussions

            QUESTION

            Laravel how to "properly" store & retrieve models in a Redis hash
            Asked 2021-Jul-08 at 17:02

            I'm developing a Laravel application & started using Redis as a caching system. I'm thinking of caching the data of all of a specific model I have, as a user may make an API request that this model is involved in quite often. Would a valid solution be storing each model in a hash, where the field is that record's unique ID, and the values are just the unique model's data, or is this use case too complicated for a simple key value database like Redis? I"m also curious as to how I would create model instances from the hash, when I retrieve all the data from it. Replies are appreciated!

            ...

            ANSWER

            Answered 2021-Jul-08 at 17:02

            Short answer: Yes, you can store a model, or collections, or basically anything in the key-value caching of Redis. As long as the key provided is unique and can be retraced. Redis could even be used as a primary database.

            Long answer

            Ultimately, I think it depends on the implementation. There is a lot of optimization that can be done before someone can/should consider caching all models. For "simple" records that involve large datasets, I would advise to first optimize your queries and code and check the results. Examples:

            1. Select only data you need, not entire models.
            2. Use the Database Query Builder for interacting with the database when targeting large records, rather than Eloquent (Eloquent is significantly slower due to the Active Record pattern).
            3. Consider using the toBase() method. This retrieves all data but does not create the Eloquent model, saving precious resources.
            4. Use tools like the Laravel debugbar to analyze and discover potential long query loads.

            For large datasets that do not change often or optimization is not possible anymore: caching is the way to go!

            There is no right answer here, but maybe this helps you on your way! There are plenty of packages that implement similar behaviour.

            Source https://stackoverflow.com/questions/68305332

            QUESTION

            Can compacted Kafka topic be used as key-value database?
            Asked 2020-Nov-25 at 01:12

            In many articles, I've read that compacted Kafka topics can be used as a database. However, when looking at the Kafka API, I cannot find methods that allow me to query a topic for a value based on a key.

            So, can a compacted Kafka topic be used as a (high performance, read-only) key-value database?

            In my architecture I want to feed a component with a compacted topic. And I'm wondering whether that component needs to have a replica of that topic in its local database, or whether it can use that compacted topic as a key value database instead.

            ...

            ANSWER

            Answered 2020-Nov-25 at 01:12

            Compacted kafka topics themselves and basic Consumer/Producer kafka APIs are not suitable for a key-value database. They are, however, widely used as a backstore to persist KV Database/Cache data, i.e: in a write-through approach for instance. If you need to re-warmup your Cache for some reason, just replay the entire topic to repopulate.

            In the Kafka world you have the Kafka Streams API which allows you to expose the state of your application, i.e: for your KV use case it could be the latest state of an order, by the means of queriable state stores. A state store is an abstraction of a KV Database and are actually implemented using a fast KV database called RocksDB which, in case of disaster, are fully recoverable because it's full data is persisted in a kafka topic, so it's quite resilient as to be a source of the data for your use case.

            Imagine that this is your Kafka Streams Application architecture:

            To be able to query these Kafka Streams state stores you need to bundle an HTTP Server and REST API in your Kafka Streams applications to query its local or remote state store (Kafka distributes/shards data across multiple partitions in a topic to enable parallel processing and high availability, and so does Kafka Streams). Because Kafka Streams API provides the metadata for you to know in which instance the key resides, you can surely query any instance and, if the key exists, a response can be returned regardless of the instance where the key lives.

            With this approach, you can kill two birds in a shot:

            1. Do stateful stream processing at scale with Kafka Streams
            2. Expose its state to external clients in a KV Database query pattern style

            All in a real-time, highly performant, distributed and resilient architecture.

            The images were sourced from a wider article by Robert Schmid where you can find additional details and a prototype to implement queriable state stores with Kafka Streams.

            Notable mention:

            If you are not in the mood to implement all of this using the Kafka Streams API, take a look at ksqlDB from Confluent which provides an even higher level abstraction on top of Kafka Streams just using a cool and simple SQL dialect to achieve the same sort of use case using pull queries. If you want to prototype something really quickly, take a look at this answer by Robin Moffatt or even this blog post to get a grip on its simplicity.

            While ksqlDB is not part of the Apache Kafka project, it's open-source, free and is built on top of the Kafka Streams API.

            Source https://stackoverflow.com/questions/64996101

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install redis-processing

            Redis-Wrapper v1.1.2 includes Jedis v3.0.0 with Redis v2.8.5 support.

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