Using Dataiku
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- When developing a python recipe, what is the best way to do the debugging? Does it make sense develop the recipe within the notebook environment and the copy the code into the recipe? Are there any de…
Last answer by MattscoHi,
Yes you are right: I code in the ipython notebook and copy paste it when I'm done.
Don't forget to specify the input and output in your recipe.
The shortcut Shift-m allows to concatenate all ipython cells of your notebook and to copy them in one shot.Last answer by MattscoHi,
Yes you are right: I code in the ipython notebook and copy paste it when I'm done.
Don't forget to specify the input and output in your recipe.
The shortcut Shift-m allows to concatenate all ipython cells of your notebook and to copy them in one shot. - I find the graphing capabilities within dataiku a bit limited. Thus I thought to use plot within a python recipe, however the output graph is not shown? How is it possible to plot within a python reci…Last answer by MattscoHi,
You can't plot anything in a python recipe.
Here are some options:
- Save your plot in a png file in your python recipe and display it in an insight.
- Use an ipython notebook.
- And of course, plot the output dataset of a Python recipe in the DSS interface, but that is what you wanted to avoid.Last answer by MattscoHi,
You can't plot anything in a python recipe.
Here are some options:
- Save your plot in a png file in your python recipe and display it in an insight.
- Use an ipython notebook.
- And of course, plot the output dataset of a Python recipe in the DSS interface, but that is what you wanted to avoid. - I would like to create a table by SQL query: CREATE TABLE `export_cellule_mysql`( `site_id` varchar(127), `latitude_WGS84` float(127), `longitude_WGS84` float(127), `lambet_X` varchar(127) `dr` varcha…Last answer by
Last answer by Clément_StenacHi,
Let me summarize how interaction with SQL works in DSS. You have very different kinds of things:
* The DATASET : it gets the rows of a SQL table, or the results of a SQL query, and makes them available as a dataset, ie, as a list of rows that you can see, process, export, visualize, ...
* The RECIPE: the "SQL Query" recipe is used to create a new dataset (stored anywhere), as the results of a SQL Query. The target dataset can be either a SQL table, or just any kind of dataset you want.
So, a DATASET is more like access on existing data, while one uses a RECIPE to create a new dataset from existing datasets, in a reproducible Flow.
More information about the SQL datasets: http://doc.dataiku.com/dss/latest/connecting/sql_datasets.html
More information about the SQL recipes: http://doc.dataiku.com/dss/latest/code_recipes/sql.html
The most important concept is that in both the Dataset and Recipe, it only makes sense to make SELECTs. The whole idea is to generate rows.
Now there is a third thing which is the SQL NOTEBOOK: it's simply an interactive SQL evaluation UI, where you can pass any SQL statement, and it gets executed.
If you want to create a SQL table, you can do it directly in the Notebook, but it will not be specially known by DSS, and it won't help you perform operations on it.
I would kindly suggest that you go through the tutorials that give more insight about how exactly datasets and recipes interact.
Regards, - It's good now, I can work on Dataiku. But when I would create a new dataset by creating the table with SQL query, it has an error: Connection OK, but query failed: Cannot issue data manipulation state…Last answer byLast answer by Clément_StenacHi Thu,
In a "SQL Query" recipe, you should enter a SELECT query, not an INSERT. DSS will take care on its own to actually transform the SELECT to an INSERT if the output is SQL, or to stream the results if it is not.
You might want to check:
http://doc.dataiku.com/dss/latest//code_recipes/sql.html
Best regards
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