Scala (via Snowpark)
E431030
Scala (via Snowpark) is a way to use the Scala programming language within Snowflake’s Snowpark developer framework to build and run data pipelines, transformations, and applications directly in the Snowflake Data Cloud.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Scala (via Snowpark) canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4326400 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scala (via Snowpark) Context triple: [Snowflake Data Cloud, supportsLanguage, Scala (via Snowpark)]
-
A.
Python (via Snowpark)
Python (via Snowpark) is Snowflake’s integration of the Python language for building and running data pipelines, machine learning, and other data applications directly within the Snowflake data platform.
-
B.
Java (via Snowpark)
Java (via Snowpark) is the capability within Snowflake’s Snowpark framework that lets developers write and execute data processing and analytics logic in Java directly inside the Snowflake data platform.
-
C.
Snowflake Data Cloud
Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
-
D.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
-
E.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Scala (via Snowpark) Target entity description: Scala (via Snowpark) is a way to use the Scala programming language within Snowflake’s Snowpark developer framework to build and run data pipelines, transformations, and applications directly in the Snowflake Data Cloud.
-
A.
Python (via Snowpark)
Python (via Snowpark) is Snowflake’s integration of the Python language for building and running data pipelines, machine learning, and other data applications directly within the Snowflake data platform.
-
B.
Java (via Snowpark)
Java (via Snowpark) is the capability within Snowflake’s Snowpark framework that lets developers write and execute data processing and analytics logic in Java directly inside the Snowflake data platform.
-
C.
Snowflake Data Cloud
Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
-
D.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
-
E.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
Snowflake development interface
ⓘ
Snowpark language binding ⓘ data engineering tool ⓘ |
| allows | writing business logic close to data ⓘ |
| avoids | data egress ⓘ |
| benefit |
improved performance for data workloads
ⓘ
reduced data movement ⓘ single governance plane in Snowflake ⓘ |
| category |
big data processing framework integration
ⓘ
cloud data platform tooling ⓘ |
| compatibleWith |
Snowflake security model
ⓘ
Snowflake warehouses ⓘ |
| designGoal |
bring Scala developers to Snowflake
ⓘ
enable code-first data pipelines ⓘ leverage Snowflake compute for Scala workloads ⓘ |
| developedBy | Snowflake Inc. NERFINISHED ⓘ |
| documentationAvailableAt | https://docs.snowflake.com ⓘ |
| enables |
application development in Scala on Snowflake
ⓘ
data pipeline development in Scala ⓘ data transformation logic in Scala ⓘ |
| executionLocation | inside Snowflake ⓘ |
| executionModel | in-database processing ⓘ |
| integratesWith |
Snowflake UDFs
NERFINISHED
ⓘ
Snowflake stored procedures ⓘ Snowflake tables ⓘ Snowflake views ⓘ |
| partOf | Snowpark NERFINISHED ⓘ |
| relatedTo |
Snowpark for Java
NERFINISHED
ⓘ
Snowpark for JavaScript NERFINISHED ⓘ Snowpark for Python NERFINISHED ⓘ |
| runsOn | Snowflake Data Cloud NERFINISHED ⓘ |
| supportsFeature |
DataFrame-style APIs
ⓘ
Scala collections interoperability ⓘ lazy evaluation of queries ⓘ pushdown of operations to Snowflake ⓘ stored procedures ⓘ type-safe APIs ⓘ user-defined functions ⓘ |
| supportsUseCase |
ELT
ⓘ
ETL ⓘ data applications ⓘ data pipelines ⓘ data transformations ⓘ machine learning workflows ⓘ |
| targetUser |
application developers
ⓘ
data engineers ⓘ data scientists ⓘ |
| usesLanguage | Scala NERFINISHED ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Scala (via Snowpark) Description of subject: Scala (via Snowpark) is a way to use the Scala programming language within Snowflake’s Snowpark developer framework to build and run data pipelines, transformations, and applications directly in the Snowflake Data Cloud.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.