named_struct | A drop-in replacement for Ruby 's Struct | Genomics library

 by   rohitpaulk Ruby Version: Current License: MIT

kandi X-RAY | named_struct Summary

kandi X-RAY | named_struct Summary

named_struct is a Ruby library typically used in Artificial Intelligence, Genomics applications. named_struct has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

A drop-in replacement for Ruby's Struct that supports keyword arguments
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            kandi-support Support

              named_struct has a low active ecosystem.
              It has 17 star(s) with 0 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              named_struct has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of named_struct is current.

            kandi-Quality Quality

              named_struct has 0 bugs and 0 code smells.

            kandi-Security Security

              named_struct has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              named_struct code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              named_struct is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              named_struct releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.
              named_struct saves you 17 person hours of effort in developing the same functionality from scratch.
              It has 47 lines of code, 6 functions and 3 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            named_struct Key Features

            No Key Features are available at this moment for named_struct.

            named_struct Examples and Code Snippets

            No Code Snippets are available at this moment for named_struct.

            Community Discussions

            QUESTION

            How to add array of struct to struct of array of struct in Spark scala
            Asked 2022-Mar-12 at 09:59

            I have below example

            ...

            ANSWER

            Answered 2022-Mar-12 at 09:59

            Just create a new struct from pi.opi1 and opi2

            Source https://stackoverflow.com/questions/71448314

            QUESTION

            Convert struct to map in Spark SQL
            Asked 2021-Dec-20 at 12:40

            I am trying to convert one dataset which declares a column to have a certain struct type (eg. struct) to a map type. And I would like to do it in SQL, possibly without using UDFs.

            UPDATE:

            My requirement is also that the transformation is done generically without any prior knowledge of the struct keys (in my problem I am getting data in a complex JSON, and I don't want to keep that complexity in the schema).

            Example input data:

            ...

            ANSWER

            Answered 2021-Dec-17 at 13:00

            I have found a way to do it which requires one roundtrip of serializing and parsing a json using the to_json and from_json functions. The trick is that the from_json also takes a schema argument where I use the map type.

            Also, this solution should work with spark < 3.x

            Source https://stackoverflow.com/questions/70380220

            QUESTION

            Return month name in specified locale
            Asked 2021-Nov-11 at 11:30

            Using date_format we can extract month name from a date:

            ...

            ANSWER

            Answered 2021-Nov-11 at 11:30

            Thanks to this clever guy, this is a very nice solution to return results in another language (locale):

            Source https://stackoverflow.com/questions/69905730

            QUESTION

            Spark dataset failed to resolve column after multiple join
            Asked 2021-Sep-12 at 00:27

            Suppose I have these case class

            ...

            ANSWER

            Answered 2021-Sep-12 at 00:27

            The error is being caused because the reference returned by left("office_id") no longer exists in the new projected dataset(i.e. the dataset resulting from the first join and map operation).

            If you look closer at the execution plan in the nested relation

            : +- LocalRelation , [id#40L, proj_id#41L, office_id#42L, salary#43L]

            you can observe that the reference to office_id in the left dataset is office_id#42L. However, if you look at the later execution, you will notice that this reference no longer exists in the projection

            SerializeFromObject [assertnotnull(assertnotnull(input[0, Employee, true])).id AS id#114L, assertnotnull(assertnotnull(input[0, Employee, true])).proj_id AS proj_id#115L, assertnotnull(assertnotnull(input[0, Employee, true])).office_id AS office_id#116L, assertnotnull(assertnotnull(input[0, Employee, true])).salary AS salary#117L]

            as the office_id reference available is office_id#116L.

            In order to resolve this, you could use intermediary/temporary variables eg:

            Source https://stackoverflow.com/questions/69146973

            QUESTION

            Converting a dataframe columns into nested JSON structure using pyspark
            Asked 2021-Jun-10 at 02:55

            I'm fairly new to pyspark

            My code what I have tried so far

            ...

            ANSWER

            Answered 2021-Jun-10 at 02:55

            QUESTION

            Create a select with a struct within a list pyspark
            Asked 2021-Jun-02 at 08:14

            I have the following Dataframe View df_view:

            ...

            ANSWER

            Answered 2021-Jun-02 at 08:14

            You can wrap the struct in array():

            Source https://stackoverflow.com/questions/67796650

            QUESTION

            Update table in Apache Spark / Databricks using multiple columns
            Asked 2020-Nov-19 at 18:16

            I'm trying to update a table based on a match to another table for multiple columns. I've tried what is shown below but I'm getting the error shown. How is this done?

            ...

            ANSWER

            Answered 2020-Oct-30 at 00:19

            First off, make sure you are using Delta Lake as the table format. Second, I think you are looking for Upserts, which are defined as

            An operation that inserts rows into a database table if they do not already exist, or updates them if they do.

            To do so you'll need to use MERGE combined with UPDATE. Here's an example with the matching expression:

            Source https://stackoverflow.com/questions/64574550

            QUESTION

            How to create an array of structs spark sql
            Asked 2020-Oct-10 at 02:15

            I am trying to create an array type. my code seems to be returning what I want but when I open up the json file the array only contains 1 struct.

            ...

            ANSWER

            Answered 2020-Oct-10 at 02:15

            I am supposed to have a narrow query.

            Source https://stackoverflow.com/questions/64288504

            QUESTION

            How to convert a DataFrame map column to a struct column?
            Asked 2020-Jun-05 at 16:03

            Suppose we have a DataFrame with a column of map type. What is the most straightforward way to convert it to a struct (or, equivalently, define a new column with the same keys and values but as a struct type)? See the following spark-shell (2.4.5) session, for an insanely inefficient way of going about it:

            ...

            ANSWER

            Answered 2020-Jun-05 at 15:18

            I would use explode function:

            Source https://stackoverflow.com/questions/62218496

            QUESTION

            Spark INLINE Vs. LATERAL VIEW EXPLODE differences?
            Asked 2020-May-30 at 08:14

            In Spark, for the following use case, I'd like to understand what are the main differences between using the INLINE and EXPLODE ... I'm not sure if there are any performance implications or if one method is preferred over the other one or if there are any other uses cases where one is appropriate and the other is not...

            The use case is to select 2 fields from a complex data type (array of structs), my instinct was to use INLINE since it explodes an array of structs

            For example:

            ...

            ANSWER

            Answered 2020-May-30 at 08:14

            EXPLODE UDTF will generate rows of struct (single column of type struct), and to get person name you need to use person.name:

            Source https://stackoverflow.com/questions/62053835

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install named_struct

            NamedStruct is available as a RubyGem. To install, run:.

            Support

            Bug reports and pull requests are welcome on GitHub at https://github.com/rohitpaulk/named_struct. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.
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            gh repo clone rohitpaulk/named_struct

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