mongo

Mongo Backend

Component provides ItemProcessor and ItemWriter for storing Feed Entries into Mongo DB.

Job Configuration

The access to DB is configurable via jobs properties: Configuration:

1. mongoUrl - Mongo URL
2. db - DB Name
3. collection - Collection name
4. feed - Feed Name
5. group - Group name (Optional)

Mongo DB

Indexes

Indexes are being automatically created on these fields:

1. url - unique
2. code
3. published
4. feed
5. group
6. tags

The stored Blog post in Mongo looks like this:

{
    "_id" : "auto generated object id",
    "feed" : "quarkus",
    "group" : "quarkus",
    "title" : "Emitter - Bridging the imperative and the reactive worlds",
    "code" : "emitter_bridging_the_imperative_and_the_reactive_worlds",
    "url" : "https://quarkus.io/blog/reactive-messaging-emitter/",
    "author" : "The Blogger",
    "published" : "2020-10-06T00:00:00.000Z",
    "updated" : "2020-10-06T00:00:00.000Z",
    "tags" : [ 
        "quarkus", 
        "kafka"
    ],
    "contentPreview" : "In a previous blog post about Kafka and Avro, we used an emitter to send Kafka messages...",
    "content" : "\n                In a previous blog post about <a href='www.kafka.io'>Kafka</a> and Avro, we used an emitter to send Kafka messages. In this post, we are going look at this emitter construct a little bit more closely. Injecting an Emitter Injecting an emitter is straightforward. You indicate the targeted channel, i.e., where do you...\n            "
}

Notes:

• content field can be long and can contain html formating from the original blogpost
• contentPreview is content cleaned not to contain html formating and shortened so it can be used as an preview

Job Example Usage

See feeds2mongo example