Based on our record, Apache Flink should be more popular than Apache Lucene. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I have to find a few examples of relatively small programming libraries that has been rewritten/ported to C++, C# and Java. Example: Lucene (it isn't that small, but still shows what I'm looking for). Source: over 1 year ago
He is talking about impacting the search algorithm. Putting a “+” sounds like it is negatively impacting search quality. Source: over 1 year ago
For example Lucene is a core project common to many search engines, lots of things built ontop of it. And there are similar libraries Https://lucene.apache.org/core/. Source: over 1 year ago
Full-text search Elasticsearch is built on top of Apache Lucene, an open-source information retrieval software. Apache Lucene enables Elasticsearch can perform complex full-text searches using a single or combination of word phrases against its No SQL database. - Source: dev.to / almost 2 years ago
If I had control of the back end I would implement a full-text engine such as Lucene. Generate the lookup table as a batch job and then perform the FTS when the request comes in. If you try to do this real-time, your search will take exponentially longer the larger the data set gets. Source: about 2 years ago
You should let the Apache Flink team know, they mention exactly-once processing on their home page (under "correctness guarantees") and in their list of features. [0] https://flink.apache.org/ [1] https://flink.apache.org/what-is-flink/flink-applications/#building-blocks-for-streaming-applications. - Source: Hacker News / 5 days ago
Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / about 1 month ago
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 5 months ago
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
ElasticSearch - Elasticsearch is an open source, distributed, RESTful search engine.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Google Cloud Search - Search across all your company's content in G Suite.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.
Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.