distributed tracing question about how to implement
hello,

i can't seem to get distributed tracing to work. im starting to wonder if i don't understand distributed tracing correctly.

in my frontend i am creating a transaction and a few spans to cover some js functions. one of the js functions makes a request to a backend python service. i am sendin…
hi james,

as you already figured out, custom transactions does not support automatic instrumentations (xhr, fetch, resources) which means the user would have to start span and attach it to the transaction manually.

and yes by setting { managed: true } in the starttransaction option the transaction…
Well, the only piece of the code you wrote that will be of any use for that assignment at all is the Scanner (though a BufferedReader would be my own choice for that). The instructions are pretty clearly laid out and does tell you what you need to use from that jss2 folder.



You need to read the file line by line. The first line is the input to create the BST. For the rest of the lines you will need to parse and match the command token to the appropriate action to take on the BST. String.split() will be useful for that part to separate <command> <parameters>.



So time to crack the books and get a start on it. Post specific questions if you run into trouble. Good luck! def render("show.json", %{user: user} = assigns) do

%{

data: render\_one(user, admin.userview, "user.json", assigns)

}

end

there’s no “implicit” assigns map, which all functions would automatically inherit somehow. you need to explicitly pass the assigns map onwards into rend… okay, i think i found out what is happening: <https://github.com/drtimothyaldendavis/suitesparse/issues/45> imho the best solution is to put the proxy`s to an bi

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… A couple of notes to get started:



> 
> .apply(literal\_eval)
> 
> 
> 


Wouldn't this be better as `map`?



> 
> I then re-create the Dask DF:
> 
> 
> ddf = dd.from\_pandas(ddf\_out, npartitions=nCores)
> 
> 
> 


`ddf_out` was already a dask dataframe, I don't know why you had to do this.



> 
> The columns in result seem to match those in metadir.
> 
> 
> 


The value of `result.columns` is taken from the meta you provided, no computing happens until you ask for it (dask is lazy in most operations). Does the ValueError exception not provide further information?


Here is a full example



```
x = ({'F9_07_PZ_COMP_DIRECT': '0',
  'F9_07_PZ_DIRTRSTKEY_NAME': 'DEBRA MEALY',
  'F9_07_PZ_COMP_OTHER': '0',
  'F9_07_PZ_COMP_RELATED': '0',
  'F9_07_PZ_TITLE': 'CHAIR PERSON',
  'F9_07_PZ_AVE_HOURS_WEEK': '1.00',
  'F9_07_PC_TRUSTEE_INDIVIDUAL': 'X'},
 {'F9_07_PZ_COMP_DIRECT': '0',
  'F9_07_PZ_DIRTRSTKEY_NAME': 'HELEN GORDON',
  'F9_07_PZ_COMP_OTHER': '0',
  'F9_07_PZ_COMP_RELATED': '0',
  'F9_07_PZ_TITLE': 'VICE CHAIR',
  'F9_07_PZ_AVE_HOURS_WEEK': '1.00',
  'F9_07_PC_TRUSTEE_INDIVIDUAL': 'X'})
df = pd.DataFrame({'a': x})
d = dd.from_pandas(df, 1)
meta = pd.DataFrame(columns=['F9_07_PZ_COMP_DIRECT', 
       'F9_07_PZ_DIRTRSTKEY_NAME',
       'F9_07_PZ_COMP_OTHER', 'F9_07_PZ_COMP_RELATED', 'F9_07_PZ_TITLE',
       'F9_07_PZ_AVE_HOURS_WEEK', 'F9_07_PC_TRUSTEE_INDIVIDUAL'], dtype="O")
d.map_partitions(lambda df: df.a.apply(pd.Series), meta=meta).compute()

```

How did I know what `meta` to use? I applied the function to the pandas dataframe - you might use a small piece of the dataframe to do this.


Some additional notes:


* it is an anti-pattern to load the data with pandas, pass to dask workers and then gather the whole result back to a pandas (in memory) dataframe, you are very unlikely to see a speedup this way and may incur a lot of overhead. You are better off loading with something like `dd.read_csv`, and aggregating or writing with dask functions too. Only `compute()` on something that will be small or not return anything (because it involves writing the output). The official examples do not use from\_pandas.
* string and dict processing are python methods, and so hold the interpreter lock (GIL) of any python function: threads will not actually run in parallel. To get parallelism, you need to run in processes, which is most easily achieved using <https://docs.dask.org/en/latest/setup/single-distributed.html>
* the distributed scheduler also gives you access to the dashboard, which has a lot of useful information to diagnose how your system is running. You can also configure a lot about its behaviour, in case you have firewall rules you need to obey. It's going to be sheer luck anyone is running that setup so try this. Break the problem down to smaller steps. If a step can't be accomplished then it's too big a step. Break it down further. mapping is the 3rd rail of cad software. most pd's cannot maintain gis files, etc. the best solution i've seen is what we have now. our system uses google maps (browser based) with a system layer over it. so, either it geo codes the address after the call is saved or it uses the lat/long we enter on the geo file in our system. we can also geo code officer alerts to the map. so much easier. we also have browser based maps from our gis analyst that has more parcel info but only dispatchers reference it. best bet is to add a layer over the google map with your boundaries. i actually spoke to my vendor and they are going to add a boundary layer to our stuff as well. it's a good idea. hey [@web2033](/u/web2033), you can see more about how to correctly configure functions here:

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learn how to get started, see examples, and view documentation for the modern web platform.

… so if you want to be able to run them as separate runs, you’ll still need some way of communicating between them. one mechanism we provide for that is by serializing daml values as json through the --input-file and --output-file options to daml script. so in your case, you should make sure that the … i checked in with the dns team on this one and we’re actually in the process of changing jump\_start to move to a newer system for scanning dns records which the ui uses already.

if you want to try it (the api is not documented yet), you can do this by creating the zone with jump\_start: false and th…