Feature/440 re enabled parquet import in notebook first steps.ipynb

README.md

@@ -2,20 +2,20 @@
 
 The Exasol AI Lab is a pre-configured container designed to empower data scientists. It streamlines common data science and AI tasks, including data loading, preparation, exploration, model training, and deployment. Whether you’re a seasoned practitioner or just getting started, the AI Lab provides a hassle-free experience.
 
-![Transformers Extension](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/ai-lab-screenshot.png)
+![Screenshot Transformers Extension](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/ai-lab-screenshot.png)
 
 Key Features:
-* Jupyter Notebook Environment: The heart of the AI Lab is a robust Jupyter Notebook environment. It’s where you’ll work on your data science projects.
-* Exasol Integration: Leverage Exasol’s power for your AI and machine learning use cases. The AI Lab includes essential Exasol packages, extensions, and configuration tasks.
-* Example Notebooks: Jumpstart your work with ready-to-use example notebooks. Explore classic machine learning scenarios (think scikit-learn), seamlessly integrate Exasol with AWS SageMaker, and tap into Hugging Face models directly within Exasol.
+* **Jupyter Notebook Environment**: The heart of the AI Lab is a robust Jupyter Notebook environment. It is where you will work on your AI and Data Science projects.
+* **Exasol Integration**: Leverage Exasol’s power for your AI and machine learning use cases. The AI Lab includes essential Exasol packages, extensions, and configuration tasks.
+* **Example Notebooks**: Jumpstart your work with ready-to-use example notebooks. Explore classic machine learning scenarios (think scikit-learn), seamlessly integrate Exasol with AWS SageMaker, and tap into Hugging Face models directly within Exasol.
 
-Feel free to explore the Exasol AI Lab and unleash your data science potential!
+## Getting Started
 
-The AI Lab is available in multiple [Editions](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/editions.md) involving different technology stacks, see also common [System Requirements](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/system-requirements.md).
+Feel free to explore the Exasol AI Lab and unleash your AI potential!
 
-After downloading the required files and having started the AI Lab you can connect to AI Lab's [Jupyter Service](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/jupyter.md).
+The AI Lab is available in **multiple editions**. Please visit the [User Guide](doc/user_guide/user-guide.md) and pick
+the one that is most convenient to your preferences.
 
 ## Additional Links
 
-* [Troubleshooting](doc/user_guide/troubleshooting.md)
 * [Developer Guide](https://github.com/exasol/ai-lab/blob/4.0.0/doc/developer_guide/developer_guide.md)

doc/changes/changes_4.1.0.md

@@ -4,10 +4,15 @@ Code name:
 
 ## Summary
 
+## Features
+
+* #440: Re-enabled Parquet import in notebook `first_steps.ipynb`
+
 ## Documentation
 
 * #432: Fixed structure and links in notebook first-steps
 * #337: Ensured correct spelling for AI Lab
+* #441: Added section "Getting Started" to User Guide
 
 ## Features
 

doc/user_guide/docker/docker-usage.md

@@ -59,7 +59,7 @@ Additional options
     * Additional [Limitations and security risks](prerequisites.md#enabling-exasol-ai-lab-to-use-docker-features) apply.
     * Only file system objects on the daemon machine can be mounted. This applies to ordinary directories as well as the `docker.sock`.
     * On Windows mounting `docker.sock` only works with Docker Desktop with WSL 2.
-  * You can mount the Docker Socket with `--volume /var/run/docker.sock:/var/run/docker.sock`
+  * You can mount the Docker Socket with `--volume /var/run/docker.sock:/var/run/docker.sock`, see [graphical overview](prerequisites.md).
 
 The following example uses all additional options:
 

doc/user_guide/editions.md → doc/user_guide/user-guide.md

@@ -1,4 +1,4 @@
-# AI Lab Editions
+# AI Lab User Guide
 
 Exasol AI Lab is available in multiple editions as shown in the following table.
 
@@ -9,16 +9,17 @@ Recommendations
 * In case a Docker client is available on your system then probably the Docker Edition is the best choice.
 * When you want to use the VM Edition then select an appropriate VM image format depending on the Hypervisor software available on your system.
 
-
-| Description                                       | Format(s)                                                                |
+| Edition                                           | Image(s)                                                                 |
 |---------------------------------------------------|--------------------------------------------------------------------------|
 | [AMI Edition](ami-usage.md)                       | Amazon Machine Image (AMI)                                               |
 | [Docker Edition](docker/docker-usage.md)          | Docker Image                                                             |
 | [Virtual Machine Edition](vm-edition/vm-usage.md) | VMware Virtual Machine Disk (VMDK), Virtual Hard Disk by Microsoft (VHD) |
 
-Each of the editions is associated with an _image_ in a specific format.
-
-The image contains all necessary dependencies and provides a running instance of Jupyterlab which is automatically started when booting or running the image.
+Each image contains all necessary dependencies and automatically launches Jupyterlab when booting or running the image.
 
-For download go to the [release notes](https://github.com/exasol/ai-lab/releases/latest).
+Please
+* [Download](https://github.com/exasol/ai-lab/releases/latest) your favorite image from the latest AI Lab release on GitHub,
+* Run the AI Lab as described in the resp. documentation for the edition, and
+* Connect to AI Lab's [Jupyter Service](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/jupyter.md).
 
+In case of problems, please refer to our [Troubleshooter](troubleshooting.md).

exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/notebook/first_steps.ipynb

@@ -256,9 +256,7 @@
    "id": "0dc80445-e5c0-43c1-ae34-f16326d6fb94",
    "metadata": {},
    "source": [
-    "**Please note**: \n",
-    "* Parquet import requires using **<span style=\"color: #40a\">Exasol version 2025.\\* or higher</span>**, see [docs.exasol.com](https://docs.exasol.com/db/latest/loading_data/load_data_parquet.htm).\n",
-    "* Hence, the import is currently commented out.\n",
+    "**Please note**: Parquet import via SQL statement `IMPORT` requires using **<span style=\"color: #40a\">Exasol version 2025.\\* or higher</span>**, see [docs.exasol.com](https://docs.exasol.com/db/latest/loading_data/load_data_parquet.htm).\n",
     "\n",
     "Now we can import the Parquet file from S3 into the database:"
    ]
@@ -271,10 +269,9 @@
    "outputs": [],
    "source": [
     "%%sql \n",
-    "SELECT 1 -- avoid error from empty cell \n",
     "\n",
-    "-- IMPORT INTO US_FLIGHTS FROM PARQUET AT AI_LAB_FIRST_STEPS_S3 \n",
-    "--    FILE 'first_steps/US_FLIGHTS_FEB_2024.parquet'"
+    "IMPORT INTO US_FLIGHTS FROM PARQUET AT AI_LAB_FIRST_STEPS_S3 \n",
+    "    FILE 'first_steps/US_FLIGHTS_FEB_2024.parquet'"
    ]
   },
   {
@@ -305,11 +302,6 @@
     "\n",
     "[PyExasol](https://exasol.github.io/pyexasol/master/index.html) is the basic Python connector for interacting with Exasol databases.\n",
     "\n",
-    "Please note\n",
-    "* Using PyExasol's import or export functions with Exasol database versions `2025.*` and higher requires Pyexasol version ≥ `1.2`.\n",
-    "* AI Lab currently is shipped with pyexasol version `0.27.0`.\n",
-    "* Hence, the Pyexasol examples can only be executed with Exasol database versions < `2025`.\n",
-    "\n",
     "### 3.1 Importing a CSV File from the Local Filesystem\n",
     "\n",
     "This section demonstrates how to import a CSV file from the local file system into the database using Pyexasol.\n",
@@ -456,8 +448,8 @@
    "metadata": {},
    "source": [
     "**Please note**: \n",
-    "* Parquet import requires using **<span style=\"color: #40a\">Exasol version 2025.\\* or higher</span>**, see [docs.exasol.com](https://docs.exasol.com/db/latest/loading_data/load_data_parquet.htm).\n",
-    "* Hence, the import is currently commented out.\n",
+    "* Parquet import via SQL statement `IMPORT` requires using **<span style=\"color: #40a\">Exasol version 2025.\\* or higher</span>**, see [docs.exasol.com](https://docs.exasol.com/db/latest/loading_data/load_data_parquet.htm).\n",
+    "* This restriction does not apply when using PyExasol's native function [import_from_parquet()](https://exasol.github.io/pyexasol/master/user_guide/exploring_features/import_and_export/index.html#id8).\n",
     "\n",
     "Now we can import the Parquet file from S3 into the database:"
    ]
@@ -471,17 +463,17 @@
    "source": [
     "from exasol.nb_connector.connections import open_pyexasol_connection\n",
     "\n",
-    "query = \"IMPORT INTO {table!q} FROM PARQUET AT {connection} FILE {file!s}\"\n",
+    "query = \"IMPORT INTO {table!q} FROM PARQUET AT {connection!r} FILE {file!s}\"\n",
     "\n",
     "params = {\n",
     "    \"table\": (ai_lab_config.db_schema, \"US_FLIGHTS\"),\n",
     "    \"connection\": \"AI_LAB_FIRST_STEPS_S3\",\n",
     "    \"file\": \"first_steps/US_FLIGHTS_FEB_2024.parquet\",\n",
     "}\n",
     "\n",
-    "#with open_pyexasol_connection(ai_lab_config, compression=True) as conn:\n",
-    "#    result = conn.execute(query, params)\n",
-    "#print(f\"Imported {result.rowcount()} rows.\")"
+    "with open_pyexasol_connection(ai_lab_config, compression=True) as conn:\n",
+    "    result = conn.execute(query, params)\n",
+    "print(f\"Imported {result.rowcount()} rows.\")"
    ]
   },
   {
@@ -578,9 +570,7 @@
    "id": "d11dcb6d-d3e5-4e1e-8d61-ba59897c56e9",
    "metadata": {},
    "source": [
-    "**Please note**: \n",
-    "* Parquet import requires using **<span style=\"color: #40a\">Exasol version 2025.\\* or higher</span>**, see [docs.exasol.com](https://docs.exasol.com/db/latest/loading_data/load_data_parquet.htm).\n",
-    "* Hence, the import is currently commented out.\n",
+    "**Please note**: Parquet import via SQL statement `IMPORT` requires using **<span style=\"color: #40a\">Exasol version 2025.\\* or higher</span>**, see [docs.exasol.com](https://docs.exasol.com/db/latest/loading_data/load_data_parquet.htm).\n",
     "\n",
     "Now we can import the Parquet file from S3 into the database:"
    ]
@@ -604,9 +594,9 @@
     "    )\n",
     ")\n",
     "\n",
-    "# with engine.connect() as conn:\n",
-    "#     result = conn.execute(t)\n",
-    "# print(f\"Imported {result.rowcount} rows.\")"
+    "with engine.connect() as conn:\n",
+    "    result = conn.execute(t)\n",
+    "print(f\"Imported {result.rowcount} rows.\")"
    ]
   },
   {