feat(sql): upgrades to querying external parquet files#6369
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feat(sql): upgrades to querying external parquet files#6369
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This reverts commit 0bef6a1.
…arquet_projection
nwoolmer
added
SQL
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# Conflicts: # core/src/main/java/io/questdb/griffin/engine/functions/catalogue/FilesFunctionFactory.java # core/src/main/java/io/questdb/griffin/engine/functions/regex/GlobStrFunctionFactory.java # core/src/main/java/io/questdb/griffin/engine/functions/table/GlobFilesFunctionFactory.java # core/src/test/java/io/questdb/test/griffin/engine/functions/table/GlobFilesFunctionFactoryTest.java # core/src/test/java/io/questdb/test/griffin/engine/functions/table/GlobFilesIntegrationTest.java
# Conflicts: # core/src/main/java/io/questdb/griffin/SqlOptimiser.java
puzpuzpuz
reviewed
Dec 16, 2025
| fromParquetColumnIndexes.setAll(metadataIndex, -1); | ||
| for (int i = 0, n = addressCache.getColumnCount(); i < n; i++) { | ||
| final int columnIndex = addressCache.getColumnIndexes().getQuick(i); | ||
| final int parquetColumnIndex = toParquetColumnIndexes.getQuick(columnIndex); |
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Table reader column indexes and parquet column indexes may not match. That's why we have this additional indirection via toParquetColumnIndexes.
This was referenced Dec 18, 2025
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WIP for parquet usability roadmap. Not ready for review, lots of refactoring required.
Closes #5280
Projection
Lack of projection causes high memory usage and slow queries when working with large parquet files. This PR aims to address this, by pushing down projections from higher query models directly to the record and page frame cursors.
Q1 Clickbench and hits.parquet
Note: This PR does change some of the permissiveness around Parquet metadata validation. Previously, it was required that the file was always fully decoded and the metadata matched exactly. Now only the projected columns must be readable from the file. Therefore, if you change the schema by changing an underlying column type, it will throw an exception. But if you add an extra column to the schema, it will simply be ignored.
Glob/hive-partitioned reads
Generally, large parquet datasets will come in a partitioned form. Querying this is unergonomic, so usually a means to query the files using a wildcard pattern is provided. For example:
Min/max statistics inc. timestamp intrinsics
Changelist
Out of scope - minmax stats etc. separate holistic PR required.