Free Apache HiveQL Formatter & Beautifier Online
Format HiveQL queries, LATERAL VIEWs, PARTITION BY, and CLUSTER BY clauses. AST-verified formatting with Monaco Git Diff inspection.
About Apache Hive SQL formatting
Apache HiveQL is built around distributed table processing and has syntax that reflects partitioned data and MapReduce-era execution. LATERAL VIEW and EXPLODE turn complex collections into rows, while PARTITIONED BY, CLUSTER BY, DISTRIBUTE BY, and SORT BY describe how data is stored or shuffled. Hive scripts may also include table DDL, INSERT OVERWRITE statements, and multiple semicolon-separated commands, so preserving statement boundaries is essential.
This Hive formatter organizes those clauses without treating them as generic ORDER BY or JOIN syntax. Generator expressions remain attached to LATERAL VIEW, distribution and sorting clauses are displayed separately, and complex ARRAY, MAP, and STRUCT constructors keep their nesting. Partition filters and window expressions receive consistent indentation so readers can distinguish a storage partition predicate from an analytic partition definition.
The Hive editor is preloaded with a query that explodes an item collection, computes a window count, filters by a date partition, and clusters the result. Use it for legacy warehouse maintenance, migration planning, or a review of HiveQL copied from an orchestration job. Format the script and open the diff to check each clause boundary before putting the cleaned SQL back into your pipeline.
It is especially helpful when a legacy query has accumulated several years of manual edits.
The resulting layout gives maintainers a reliable map of the original HiveQL behavior.
For older Hive estates, readable layout is an important maintenance aid because storage and shuffle clauses can look similar at a glance. The dedicated page keeps those choices visible so a cleanup pass does not hide the operational behavior of a legacy job.
That makes the formatter suitable for both a single Hive query and a larger orchestration script. The output clarifies which expressions shape rows, which predicates use partitions, and which clauses control distribution or sorting in the warehouse.
What's different about Apache Hive formatting? HiveQL formatting separates LATERAL VIEW expansion from partition, distribution, and cluster clauses used by warehouse jobs. Example: SELECT item_name FROM raw_records LATERAL VIEW EXPLODE(items) item_table AS item_name CLUSTER BY dept_id;
Apache Hive formatting highlights
- HiveQL LATERAL VIEW and EXPLODE expressions
- CLUSTER BY, DISTRIBUTE BY, and SORT BY clauses
- Partitioned table queries
- Complex type constructors (ARRAY, MAP, STRUCT)
Hive partition and cluster clauses are laid out cleanly. The editor above is already configured for Apache Hive; format the included sample or replace it with a query from your own project.
Apache Hive formatter FAQ
Does this support CLUSTER BY and DISTRIBUTE BY in Hive?
Yes, Hive-specific sorting and distribution clauses are fully supported.
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