Hi I am very new to Databricks and wanted some guidance. I trying to pass in some parameters into a Databricks Notebook and I want it to do some simple computations. For example, pass in two parameters, x and y => return x + y as a response. I tried looking into it but couldn't find anything concrete.
You may consider looking into Databricks widgets.
Reference: https://docs.databricks.com/notebooks/widgets.html
Related
Question is simple:
master_dim.py calls dim_1.py and dim_2.py to execute in parallel. Is this possible in databricks pyspark?
Below image is explaning what am trying to do, it errors for some reason, am i missing something here?
Just for others in case they are after how it worked:
from multiprocessing.pool import ThreadPool
pool = ThreadPool(5)
notebooks = ['dim_1', 'dim_2']
pool.map(lambda path: dbutils.notebook.run("/Test/Threading/"+path, timeout_seconds= 60, arguments={"input-data": path}),notebooks)
your problem is that you're passing only Test/ as first argument to the dbutils.notebook.run (the name of notebook to execute), but you don't have notebook with such name.
You need either modify list of paths from ['Threading/dim_1', 'Threading/dim_2'] to ['dim_1', 'dim_2'] and replace dbutils.notebook.run('Test/', ...) with dbutils.notebook.run(path, ...)
Or change dbutils.notebook.run('Test/', ...) to dbutils.notebook.run('/Test/' + path, ...)
Databricks now has workflows/multitask jobs. Your master_dim can call other jobs to execute in parallel after finishing/passing taskvalue parameters to dim_1, dim_2 etc.
I have python variable created under %python in my jupyter notebook file in Azure Databricks. How can I access the same variable to make comparisons under %sql. Below is the example:
%python
RunID_Goal = sqlContext.sql("SELECT CONCAT(SUBSTRING(RunID,1,6),SUBSTRING(RunID,1,6),'01_')
FROM RunID_Pace").first()[0]
AS RunID_Goal
%sql
SELECT Type , KPIDate, Value
FROM table
WHERE
RunID = RunID_Goal (This is the variable created under %python and want to compare over here)
When I run this it throws an error:
Error in SQL statement: AnalysisException: cannot resolve 'RunID_Goal' given input columns:
I am new azure databricks and spark sql any sort of help would be appreciated.
One workaround could be to use Widgets to pass parameters between cells. For example, on Python side it could be as following:
# generate test data
import pyspark.sql.functions as F
spark.range(100).withColumn("rnd", F.rand()).write.mode("append").saveAsTable("abc")
# set widgets
import random
vl = random.randint(0, 100)
dbutils.widgets.text("my_val", str(vl))
and then you can refer the value from the widget inside the SQL code:
%sql
select * from abc where id = getArgument('my_val')
will give you:
Another way is to pass variable via Spark configuration. You can set variable value like this (please note that that the variable should have a prefix - in this case it's c.):
spark.conf.set("c.var", "some-value")
and then from SQL refer to variable as ${var-name}:
%sql
select * from table where column = '${c.var}'
One advantage of this is that you can use this variable also for table names, etc. Disadvantage is that you need to do the escaping of the variable, like putting into single quotes for string values.
You cannot access this variable. It is explained in the documentation:
When you invoke a language magic command, the command is dispatched to the REPL in the execution context for the notebook. Variables defined in one language (and hence in the REPL for that language) are not available in the REPL of another language. REPLs can share state only through external resources such as files in DBFS or objects in object storage.
Here is another workaround.
# Optional code to use databricks widgets to assign python variables
dbutils.widgets.text('my_str_col_name','my_str_col_name')
dbutils.widgets.text('my_str_col_value','my_str_col_value')
my_str_col_name = dbutils.widgets.get('my_str_col_name')
my_str_col_value = dbutils.widgets.get('my_str_col_value')
# Query with string formatting
query = """
select *
from my_table
where {0} < '{1}'
"""
# Modify query with the values of Python variable
query = query.format(my_str_col_name,my_str_col_value)
# Execute the query
display(spark.sql(query))
A quick complement to answer.
Do you can use widgets to pass parameters to another cell using magic %sql, as was mentioned;
dbutils.widgets.text("table_name", "db.mytable")
And at the cell that you will use this variable do you can use $ shortcut ~ getArgument isn't supported;
%sql
select * from $table_name
My question is how to assign variables within a loop in KQL magic command in Jupyter lab. I refer to Microsoft's document on this subject and will base my question on the code given here:
https://learn.microsoft.com/en-us/azure/data-explorer/kqlmagic
1. First query below
%%kql
StormEvents
| summarize max(DamageProperty) by State
| order by max_DamageProperty desc
| limit 10
2. Second: Convert the resultant query to a dataframe and assign a variable to 'statefilter'
df = _kql_raw_result_.to_dataframe()
statefilter =df.loc[0].State
statefilter
3. This is where I would like to modify the above query and let statefilter have multiple variables (i.e. consist of different states):
df = _kql_raw_result_.to_dataframe()
statefilter =df.loc[0:3].State
statefilter
4. And finally I would like to run my kql query within a for loop for each of the variables within statefilter. This below syntax may not be correct but it can give an example for what I am looking for:
dfs = [] # an empty list to store dataframes
for state in statefilters:
%%kql
let _state = state;
StormEvents
| where State in (_state)
| do some operations here for that specific state
df = _kql_raw_result_.to_dataframe()
dfs.append(df) # store the df specific to state in the list
The reason why I am not querying all the desired states within the KQL query is to prevent resulting in really large query outcomes being assigned to dataframes. This is not for this sample StormEvents table which has a reasonable size but for my research data which consists of many sites and is really big. Therefore I would like to be able to run a KQL query/analysis for each site within a for loop and assign each site's query results to a dataframe. Please let me know if this is possible or perhaps there may other logical ways to do this within KQL...
There are few ways to do it.
The simplest is to refractor your %%kql cell magic to a %kql line magic.
Line magic can be embedded in python cell.
Other option is to: from Kqlmagic import kql
The Kqlmagic kql method, accept as a string a kql cell or line.
You can call kql from python.
Third way is to call the kql magic via the ipython method:
ip.run_cell_magic('kql', {your kql magic cell text})
You can call it from python.
Example of using the single line magic mentioned by Michael and a return statement that converted the result to JSON. Without the conversion to JSON I wasn't getting anything back.
def testKQL():
%kql DatabaseName | take 10000
return _kql_raw_result_.to_dataframe().to_json(orient='records')
I've loaded a couple of functions (f and g) from another script in my jupyter notebook. if I pass the parameters, I am able to get the proper output. My question is, is it possible for me to see the whole definition of the function (f or g)?
I tried to see the function but it shows the memory location that was assigned to it.
You can do this with the built in inspect library.
The below snippet should get you acquainted with how to see the source code of a function.
def hello_world():
print("hello_world")
import inspect
source = inspect.getsource(hello_world)
print(source)
You need to comment your function inside (check docstring, https://www.python.org/dev/peps/pep-0257/) like
def func(a,b):
"""
Wonderful
"""
return a+b
Then in your jupyter notebook you can use Shift + Tab on your function.
I can not comment, but this comes from another thread How can I see function arguments in IPython Notebook Server 3?
I am currently using the pySpark console to play around with Spark and I was wondering if there is a way to list all functions that were define by me?
Currently I am forced to scroll all the way up to the definition of the function which can be tedious if you have a lot of output to scroll over.
Thank you so much for your help!
Keeping your workspace clean makes more sense but if you really need something like this you can filter variables in the current scope:
[k for (k, v) in globals().items() if (
callable(v) and # function or callable object
getattr(v, "__module__", None) == "__main__" and # defined in __main__
not k.startswith("_") # not hidden
)]