chore(extensions-docs): update extensions doc assets to recent develo…

…pment state (#147)

Co-authored-by: dominikriemer <[email protected]>

docs/pe/org.apache.streampipes.processors.transformation.jvm.datetime.md

@@ -0,0 +1,78 @@
+---
+id: org.apache.streampipes.processors.transformation.jvm.datetime
+title: Datetime From String
+sidebar_label: Datetime From String
+---
+
+<!--
+  ~ Licensed to the Apache Software Foundation (ASF) under one or more
+  ~ contributor license agreements.  See the NOTICE file distributed with
+  ~ this work for additional information regarding copyright ownership.
+  ~ The ASF licenses this file to You under the Apache License, Version 2.0
+  ~ (the "License"); you may not use this file except in compliance with
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+  ~    http://www.apache.org/licenses/LICENSE-2.0
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+  ~ See the License for the specific language governing permissions and
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+  ~
+  -->
+
+
+
+<p align="center">
+    <img src="/img/pipeline-elements/org.apache.streampipes.processors.transformation.jvm.datetime/icon.png" width="150px;" class="pe-image-documentation"/>
+</p>
+
+***
+
+## Overview
+
+The "Datetime From String" processor is a handy tool that helps convert human-readable datetime information into a
+format that machines can understand. This is particularly useful when dealing with data that includes dates and times.
+
+### Why Use This Processor?
+
+In the context of event streams, you may encounter dates and times formatted for human readability but not necessarily
+optimized for computer processing. The "Datetime From String" processor addresses this by facilitating the conversion
+of human-readable datetime information within your continuous stream of events.
+
+***
+
+## How It Works
+
+When you input a data stream into this processor containing a datetime in a specific format (such as "2023-11-24 15:30:
+00"), it
+undergoes a transformation. The processor converts it into a computer-friendly format called a ZonedDateTime object.
+
+### Example
+
+Let's say you have an event stream with a property containing values like "2023-11-24 15:30:00" and you want to make
+sure your computer understands it. You can use
+this processor to convert it into a format that's machine-friendly.
+
+***
+
+## Getting Started
+
+To use this processor, you need one thing in your data:
+
+1. **Datetime String**: This is the name of the event property that contains the human-readable datetime string, like "2023-11-24 15:30:00".
+
+
+### Configuration
+
+The only thing you need to configure is the time zone.
+1. **Time Zone**: Specify the time zone that applies to your datetime if it doesn't already have this information.This ensures that the processor understands the context of your
+datetime.
+
+## Output
+
+After the conversion happens, the processor adds a new piece of information to your data stream:
+
+* **timestringInMillis**: This is the transformed datetime in a format that computers can easily work with (UNIX timestamp in milliseconds).
+* **timeZone**: The name of the timezone the `dateTime` value refers to. Can be used to reconstitute the actual time.

docs/pe/org.apache.streampipes.sinks.internal.jvm.datalake.md

@@ -33,7 +33,8 @@ sidebar_label: Data Lake
 ## Description
 
 Stores events in the internal data lake so that data can be visualized in the live dashboard or in the data explorer.
-Simply create a pipeline with a data lake sink, switch to one of the data exploration tool and start exploring your data!
+Simply create a pipeline with a data lake sink, switch to one of the data exploration tool and start exploring your
+data!
 
 ***
 
@@ -46,7 +47,22 @@ This sink requires an event that provides a timestamp value (a field that is mar
 
 ## Configuration
 
-### Index
+### Identifier
 
-The name of the storage group of this event. 
+The name of the measurement (table) where the events are stored.
 
+### Schema Update Options
+
+The Schema Update Options dictate the behavior when encountering a measurement (table) with the same identifier.
+
+#### Option 1: Update Schema
+
+- **Description:** Overrides the existing schema.
+- **Effect on Data:** The data remains in the data lake, but accessing old data is restricted to file export.
+- **Impact on Features:** Other StreamPipes features, such as the Data Explorer, will only display the new event schema.
+
+#### Option 2: Extend Existing Schema
+
+- **Description:** Keeps old event fields in the event schema.
+- **Strategy:** This follows an append-only strategy, allowing continued work with historic data.
+- **Consideration:** Old properties may exist for which no new data is generated.

website-v2/sidebars.json

@@ -70,6 +70,7 @@
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           "pe/org.apache.streampipes.processors.transformation.jvm.count-array",
           "pe/org.apache.streampipes.processors.siddhi.count",
+          "pe/org.apache.streampipes.processors.transformation.jvm.datetime",
           "pe/org.apache.streampipes.processors.transformation.jvm.fieldhasher",
           "pe/org.apache.streampipes.processors.transformation.jvm.field-mapper",
           "pe/org.apache.streampipes.processors.transformation.jvm.fieldrename",