partiql-lang-kotlin
krangl
partiql-lang-kotlin | krangl | |
---|---|---|
6 | 1 | |
532 | 559 | |
-0.2% | - | |
9.3 | 6.9 | |
4 days ago | over 1 year ago | |
Kotlin | Kotlin | |
Apache License 2.0 | MIT License |
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partiql-lang-kotlin
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Amazon Ion Specification
Ion is heavily used on the retail side of Amazon, but it's only recently started to appear in AWS products.
AWS is starting support PartiQL (https://partiql.org/) queries in some places and PartiQL uses Ion's type system internally.
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XTDB ‘Core2’ is an experimental, SQL-first, immutable database concept
Yep, that's exactly the vision here. One of the biggest sources of precedent and inspiration for us here is https://partiql.org/ which is picking up a fair bit of traction across AWS. Also see https://rockset.com/
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What is a Quantum Ledger Database?
QLDB allows you to create a ledger that acts similar to a schema or table space in a traditional database. Once you've created this ledger, you create a table through the SQL-like query language PartiQL that also enables you to interact with the data.
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Show HN: PRQL – A Proposal for a Better SQL
PartiQL[0] is an open source library that is a superset of SQL that I really like. It supports querying nested structures inside columns, so if a column contains some JSON data you can use the standard dot notation to query nested JSON data directly
[0] https://partiql.org/
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DynamoDB with PartiQL
PartiQL was introduced to AWS DynamoDB, with AWS making the announcement in 2020 making the life of developers easier, with the comfort of executing commands similar to SQL.
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Newcomer needs help with Dynamodb (PARTIQL)
I haven't tried it, but I'm pretty sure the problem is that timestamp (and it's various capitalizations) is a keyword in PartiQL (https://github.com/partiql/partiql-lang-kotlin/blob/master/lang/src/org/partiql/lang/syntax/LexerConstants.kt#L221). To get it to be interpreted as an attribute name, you need to enclose TimeStamp in double quotes.
krangl
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2,900 page Manual about Pandas [pdf]
> And what's the alternative, Excel?
Take this with a grain of salt from someone who needs data manipulation occasionally every now and then (as opposed to being a full time number-cruncher, data-scientist, statistician etc.), using krangl[1] for Kotlin has been a great experience.
I was drawn to this library because I use Kotlin in my dayjob for backend development, but I love how well Kotlin's succinct syntax & features like extension functions lends itself to data transformation & ETL kind of use cases.
Also it doesn't hurt that JVM has a plethora of libraries available for things like DB access, plotting, etc.
I am sure that Pandas has many features I am unaware of, and for a lot of people the high-ish startup time can be a deterrant, but for most of my day to day data munging the combination of jbang, krangl & kravis has been a pretty good fit.
[1] https://github.com/holgerbrandl/krangl
What are some alternatives?
rfcs - RFCs for major changes to EdgeDB
Kotlift - Kotlift is the first source-to-source language transpiler from Kotlin to Swift
malloy - Malloy is an experimental language for describing data relationships and transformations.
kassava - This library provides some useful kotlin extension functions for implementing toString(), hashCode() and equals() without all of the boilerplate.
tresql - Shorthand SQL/JDBC wrapper language, providing nested results as JSON and more
kotlin-logging - Lightweight Multiplatform logging framework for Kotlin. A convenient and performant logging facade.
partiql-ir-generator - PartiQL I.R. Generator (P.I.G.)
Strukt - C-style structs on the JVM!
spyql - Query data on the command line with SQL-like SELECTs powered by Python expressions
kotlinx-datetime - KotlinX multiplatform date/time library
logica - Logica is a logic programming language that compiles to SQL. It runs on Google BigQuery, PostgreSQL and SQLite.
asmble - Compile WebAssembly to JVM and other WASM tools