kandi X-RAY | lineages Summary
kandi X-RAY | lineages Summary
Resources for calling and describing the circulating lineages of SARS-CoV-2
Top functions reviewed by kandi - BETA
- Create lineage objects from metadata file
- Parse travel history
- Generate the report
- Parse command line arguments
lineages Key Features
lineages Examples and Code Snippets
Trending Discussions on lineages
I have many text documents (
items) that consist of a unique item number (
item_nr) and a text (
The items might be linked to none, one or multiple other items over their
item_nr in the
I have a few starting items (
start_items) for which I would like to identify trees (lineages) of all linked items until their ends (an item that does not link another one).
ANSWERAnswered 2021-May-05 at 13:38
This was a fun problem to investigate :-)
Your issue is a classic problem of recursion, which is a kinda hard concept the first time you see it.
As you don't know how many recursions there will be, a
long format is better.
Here, the recursive function will call itself as long as there are links to parse. The escape condition is based on the number of remaining links. However, I added a
max_r value to avoid being stuck in an infinite loop, in the case you have an item linking to itself (directly or not).
The initiation loop (
if(r==0)) is only here to prepare the long format, where a single item can be on multiple rows: there is a source item, a current item and a current recursion number. This should be externalized to simplify the function (then you start at
r=1) if you don't care to change your dataset format.
Given the following schema, "driver-passenger" lineages can be easily seen:...
ANSWERAnswered 2020-Sep-24 at 22:25
This one seems to do the trick:
We usually use Spark as processing engines for data stored on S3 or HDFS. We use Databricks and EMR platforms. One of the issues I frequently face is when the task size grows, the job performance is degraded severely. For example, let's say I read data from five tables with different levels of transformation like (filtering, exploding, joins, etc), union subset of data from these transformations, then do further processing (ex. remove some rows based on a criteria that requires windowing functions etc) and then some other processing stages and finally save the final output to a destination s3 path. If we run this job without it takes very long time. However, if we save(stage) temporary intermediate dataframes to S3 and use this saved (on S3) dataframe for the next steps of queries, the job finishes faster. Does anyone have similar experience? Is there a better way to handle this kind of long tasks lineages other than checkpointing?
What is even more strange is for longer lineages spark throws an expected error like column not found, while the same code works if intermediate results are temporarily staged....
ANSWERAnswered 2019-Oct-27 at 01:48
Writing the intermediate data by saving the dataframe, or using a checkpoint is the only way to fix it. You're probably running into an issue where the optimizer is taking a really long time to generate the plan. The quickest/most efficient way to fix this is to use localCheckpoint. This materializes a checkpoint locally.
With interactive rebase (
git -i rebase ...) one can edit commits anywhere in the current branch's lineage, thus "rewriting history".
A given commit, however, can belong to the lineages of multiple branches.
For example, suppose I have a repo with this branch structure:...
ANSWERAnswered 2020-Feb-22 at 01:05
... is there a halfway convenient way to achieve [a sensible result]
There's one command,
git filter-branch, that can do it, but it's not halfway convenient, nor even 1/4th convenient. It's about 1000% inconvenient. :-)
git rebase --rebase-merges machinery is pretty obviously adaptable to doing this sort of thing in a more convenient way,1 but it's not currently designed to rebase multiple branch names.
The new experimental
git filter-repo is capable enough to do what you want, and probably less inconvenient than
git filter-branch, but it's still swatting bugs with nuclear weapons—in this case, maybe a moderately large bug, not just a fly, but still serious overkill.
(I once wrote my own experimental thing to do this sort of rebase, but I never finished it. It did what I needed it to, when I needed it. It worked using the equivalent of repeated
git rebase --onto operations and had a lot of corner cases.)
1The key is to be able to label particular commits, so that after rebase copies them, you can pair up the hash-ID pairs, and otherwise jump around the graph structure from one chain to another as the rebase progresses. The old
--preserve-merges code could not do that; the new
--rebase-merges code can. Once you have these pieces in place, rebasing multiple branches "simultaneously" is just a matter of saving multiple branch names to force-adjust after the rebase completes. You then have the rebase list the correct commits and jump-points. The main bulk of the rebase operation consists of copying those commits. Last, using the old-to-new mapping, rebase can adjust each branch name, then reconnect
HEAD to the one you want.
The remaining user-interface level problem lies in selecting the correct set of branch names to multi-rebase.
Here is the code:...
ANSWERAnswered 2019-Dec-06 at 18:11
Your problem resides on the declaration of
document on every function.
Your code is:
I have a Pandas DataFrame, where each row represents a link between two unique spots (source and target) within lineages. The lineages may only split into two, but they never merge:...
ANSWERAnswered 2019-Oct-24 at 08:02
We need to use df.apply functionality of pandas
I'm interested in a nice and clear representation of Spark RDD lineages or operator graphs for educational purposes. I tried
.toDebugString() but I'm having trouble getting it pretty-printed (including line breaks etc.) What is going wrong here?
ANSWERAnswered 2018-Apr-10 at 13:06
but I'm having trouble getting it pretty-printed
Because it is
bytes object. Just
decode the result:
No vulnerabilities reported
You can use lineages like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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