HiveQL
E705291
HiveQL is a SQL-like query language designed for managing and analyzing large datasets stored in Apache Hive’s data warehouse system on Hadoop.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Apache Hive SQL dialect | 1 |
| Hive Query Language | 1 |
| HiveQL canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7985639 — 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: HiveQL Context triple: [Apache Hive, supportsLanguage, HiveQL]
-
A.
Apache Hive
Apache Hive is a data warehouse and SQL-like query system built on top of Hadoop for managing and analyzing large datasets stored in distributed storage.
-
B.
Apache Sqoop
Apache Sqoop is an open-source tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
-
C.
Apache Pig
Apache Pig is a high-level platform for creating MapReduce programs used to analyze large data sets in the Hadoop ecosystem.
-
D.
CQL
CQL (Contextual Query Language) is a formal query language designed for representing and expressing complex search queries in a human-readable, standards-based way, commonly used in information retrieval and library systems.
-
E.
KSQL
KSQL is the ICAO airport code for San Carlos Airport, a general aviation facility serving the San Francisco Bay Area in California.
- 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: HiveQL Target entity description: HiveQL is a SQL-like query language designed for managing and analyzing large datasets stored in Apache Hive’s data warehouse system on Hadoop.
-
A.
Apache Hive
Apache Hive is a data warehouse and SQL-like query system built on top of Hadoop for managing and analyzing large datasets stored in distributed storage.
-
B.
Apache Sqoop
Apache Sqoop is an open-source tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
-
C.
Apache Pig
Apache Pig is a high-level platform for creating MapReduce programs used to analyze large data sets in the Hadoop ecosystem.
-
D.
CQL
CQL (Contextual Query Language) is a formal query language designed for representing and expressing complex search queries in a human-readable, standards-based way, commonly used in information retrieval and library systems.
-
E.
KSQL
KSQL is the ICAO airport code for San Carlos Airport, a general aviation facility serving the San Francisco Bay Area in California.
- F. None of above. chosen
Statements (61)
| Predicate | Object |
|---|---|
| instanceOf |
data warehouse query language
ⓘ
domain-specific language ⓘ query language ⓘ |
| basedOn | SQL ⓘ |
| compiledTo |
Apache Spark jobs
ⓘ
Apache Tez jobs ⓘ MapReduce jobs ⓘ |
| designedFor |
Apache Hive
ⓘ
Hadoop ecosystem ⓘ |
| developedBy | Apache Software Foundation ⓘ |
| domain |
big data analytics
ⓘ
data engineering ⓘ |
| hasAlternativeName |
HQL
ⓘ
Hive Query Language ⓘ
linked to:
HiveQL
|
| hasFeature |
SQL-like syntax
ⓘ
extensibility via UDFs ⓘ support for SerDes ⓘ support for buckets ⓘ support for complex data types ⓘ support for partitions ⓘ |
| runsOn |
Apache Hive metastore
ⓘ
linked to:
Hive Metastore
Hadoop Distributed File System ⓘ
linked to:
HDFS
|
| supportsComplexType |
ARRAY
ⓘ
MAP ⓘ STRUCT ⓘ UNIONTYPE ⓘ |
| supportsDataType |
BIGINT
ⓘ
BOOLEAN ⓘ DATE ⓘ DECIMAL ⓘ DOUBLE ⓘ FLOAT ⓘ INT ⓘ STRING ⓘ TIMESTAMP ⓘ |
| supportsOperation |
DELETE
ⓘ
GROUP BY ⓘ INSERT ⓘ JOIN ⓘ LIMIT ⓘ ORDER BY ⓘ SELECT ⓘ UPDATE ⓘ bucketing ⓘ external tables ⓘ partition management ⓘ schema-on-read ⓘ subqueries ⓘ table creation ⓘ user-defined functions ⓘ views ⓘ |
| targetUser |
data analysts
ⓘ
data engineers ⓘ |
| usedFor |
ETL processing
ⓘ
ad hoc querying ⓘ batch analytics ⓘ data warehousing ⓘ |
| usedWith |
Apache Hive CLI
ⓘ
linked to:
Hive CLI
Beeline ⓘ JDBC clients ⓘ ODBC clients ⓘ |
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: HiveQL Description of subject: HiveQL is a SQL-like query language designed for managing and analyzing large datasets stored in Apache Hive’s data warehouse system on Hadoop.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: HiveQL
linked to: HiveQL