News - 16 series#

Release 16.0.8 - 2026-07-13#

Improvements#

[between] Added support for vector type value as the 1st parameter#

Note that between does not use an index for a vector value yet.

In the following example, between returns true if any of the elements is included in the specified range. Therefore, we can use between to search records that have at least one value in the range.

Execution example:

table_create Products TABLE_HASH_KEY ShortText
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Products prices COLUMN_VECTOR Int32
# [[0,1337566253.89858,0.000355720520019531],true]

load --table Products
[
{"_key": "A", "prices": [17, 170, 1700]},
{"_key": "B", "prices": [18, 180, 1800]},
{"_key": "C", "prices": [19, 190]},
{"_key": "D", "prices": [20]},
{"_key": "E", "prices": [21, 210, 2100]}
]
# [[0,1337566253.89858,0.000355720520019531],5]

select Products --filter 'between(prices, 18, "include", 20, "exclude")'
# [
#   [
#     0,
#     1337566253.89858,
#     0.000355720520019531
#   ],
#   [
#     [
#       [
#         2
#       ],
#       [
#         [
#           "_id",
#           "UInt32"
#         ],
#         [
#           "_key",
#           "ShortText"
#         ],
#         [
#           "prices",
#           "Int32"
#         ]
#       ],
#       [
#         2,
#         "B",
#         [
#           18,
#           180,
#           1800
#         ]
#       ],
#       [
#         3,
#         "C",
#         [
#           19,
#           190
#         ]
#       ]
#     ]
#   ]
# ]

Dropped support for Debian 12 (bookworm)#

It reached EOL on 2026-06-10.

Fixes#

Fixed a crash bug when we specify language_model_knn(...) as sort_keys#

For example, if you specify language_model_knn(text, "male child", {"k" : 2 }) as sort_keys, Groonga crashes due to a double free that occurs while processing the { "k" : 2 } option in the sort routine.

Fixed a crash bug when we use language_model_knn() with empty value#

Groonga crashes when language_model_knn() is used with empty value as shown below:

plugin_register language_model/knn
[[0,0.0,0.0],true]

table_create Data TABLE_NO_KEY
[[0,0.0,0.0],true]
column_create Data text COLUMN_SCALAR ShortText
[[0,0.0,0.0],true]
column_create Data rabitq_code COLUMN_SCALAR ShortBinary
[[0,0.0,0.0],true]

load --table Data
[
{"text": "I am a boy."},
{"text": ""},
{"text": "This is an apple."}
]
[[0,0.0,0.0],3]

table_create RaBitQ TABLE_HASH_KEY ShortBinary \
  --default_tokenizer 'TokenLanguageModelKNN("model", \
                                             "hf:///groonga/all-MiniLM-L6-v2-Q4_K_M-GGUF", \
                                             "code_column", "rabitq_code")'
[[0,0.0,0.0],true]
column_create RaBitQ data_text COLUMN_INDEX Data text
[[0,0.0,0.0],true]

select Data   --filter 'language_model_knn(text, "male child")'   --output_columns text

Experimental features#

This is an experimental feature. Currently, this feature is still not stable.

[json_extract] Added support for json_extract()#

json_extract() extracts values from a JSON by a JSONPath expression. The extracted values keep their JSON types. For example, a string in JSON is extracted as a text and an integer in JSON is extracted as an integer. Therefore, we can use json_extract() for both full text search against strings and range search against numbers as shown below:

table_create Data TABLE_NO_KEY
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Data value COLUMN_SCALAR JSON
# [[0,1337566253.89858,0.000355720520019531],true]

load --table Data
[
{"value": "{\"value\": [[1, 10], [100]]}"},
{"value": "{\"value\": [[2], [20, 200]]}"},
{"value": "{\"value\": [[-1, -10], [-100]]}"}
]

select Data --filter 'between(json_extract(value, "$.value[*][*]"), 10, 20)'
# [
#   [
#     0,
#     1337566253.89858,
#     0.000355720520019531
#   ],
#   [
#     [
#       [
#         2
#       ],
#       [
#         [
#           "_id",
#           "UInt32"
#         ],
#         [
#           "value",
#           "JSON"
#         ]
#       ],
#       [
#         1,
#         {
#           "value": [
#             [
#               1,
#               10
#             ],
#             [
#               100
#             ]
#           ]
#         }
#       ],
#       [
#         2,
#         {
#           "value": [
#             [
#               2
#             ],
#             [
#               20,
#               200
#             ]
#           ]
#         }
#       ]
#     ]
#   ]
# ]

[ExtractorJSON] Added support for ExtractorJSON#

This is an experimental feature. Currently, this feature is still not stable.

ExtractorJSON extracts values from JSON data by a JSONPath expression as well as json_extract(). We can use this extractor to index only the values you need from JSON without indexing the whole JSON text.

When you attach ExtractorJSON to a lexicon, the lexicon indexes the extracted values. The original JSON is kept in the data column.

The following example indexes integers in a JSON column. The lexicon key type is Int32 because the extracted values are integers. The index is used automatically when the JSON column is loaded, so you can search the original records by the extracted values:

table_create Data TABLE_NO_KEY
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Data value COLUMN_SCALAR JSON
# [[0,1337566253.89858,0.000355720520019531],true]
table_create Numbers TABLE_PAT_KEY Int32 \
  --extractors 'ExtractorJSON("path", "$.value[*][*]")'
# [[0,1337566253.89858,0.000355720520019531],true]
column_create Numbers data_value COLUMN_INDEX Data value
# [[0,1337566253.89858,0.000355720520019531],true]
load --table Data
[
{"value": "{\"value\": [[1, 10], [100]]}"},
{"value": "{\"value\": [[2], [20, 200]]}"},
{"value": "{\"value\": [[-1, -10], [-100]]}"}
]
# [[0,1337566253.89858,0.000355720520019531],3]
select Data --filter 'between(Numbers.data_value, 10, 20)'
# [
#   [
#     0,
#     1337566253.89858,
#     0.000355720520019531
#   ],
#   [
#     [
#       [
#         2
#       ],
#       [
#         [
#           "_id",
#           "UInt32"
#         ],
#         [
#           "value",
#           "JSON"
#         ]
#       ],
#       [
#         1,
#         {
#           "value": [
#             [
#               1,
#               10
#             ],
#             [
#               100
#             ]
#           ]
#         }
#       ],
#       [
#         2,
#         {
#           "value": [
#             [
#               2
#             ],
#             [
#               20,
#               200
#             ]
#           ]
#         }
#       ]
#     ]
#   ]
# ]

Release 16.0.5 - 2026-05-22#

Fixes#

Fixed a bug where Groonga for Windows failed to run due to a missing required DLL#

The required DLL (msvcp140_atomic_wait.dll) for Groonga for Windows was missing from the groonga-16.0.2-x64-vs2022-with-vcruntime.zip.

This issue only affects Groonga 16.0.2 for Windows.

Release 16.0.2 - 2026-05-07#

Improvements#

Added support for Ubuntu 26.04 LTS#

Fixes#

Fixed the ODR(One Definition Rule) violation#

GH-2787 Reported by Nicolas PARLANT.

The LTO(Link-Time Optimization) build was failing because grn_tokenizer_query had two different definitions. This change fixes the ODR violation, allowing the LTO process to complete successfully.

Fixed missing files in benchmark directory of source archive#

GH-2793 Reported by Nicolas PARLANT.

The missing files are as follows:

  • groonga/benchmark/CMakeLists.txt

  • groonga/benchmark/bench-distance.c

  • groonga/benchmark/geo-distance-summary.rb

Fixed a bug where duplicate “tools” directories were created#

GH-2798 Reported by Kentaro Hayashi.

Fixed an issue where duplicate “tools” directories were created as below when installing the groonga-tools package on AlmaLinux and Amazon Linux:

/usr/share/groonga/tools/tools/

Thanks#

  • Nicolas PARLANT

  • Kentaro Hayashi

Release 16.0.1 - 2026-03-30#

Improvements#

[language_model_vectorize] Added prefix option#

You can now add a prefix to the input text. This is useful for models that require a prefix, similar to the passage_prefix and query_prefix options of TokenLanguageModelKNN.

language_model_vectorize("hf:///groonga/multilingual-e5-base-Q4_K_M-GGUF", \
                         "male child", \
                         {"prefix": "query: "})

[object_list] Added normalizer information to the output#

object_list command now includes a normalizers field in the output for each table.

Fixes#

[HTTP] Fixed a false error for chunked HTTP requests#

Fixed a bug where valid chunked HTTP requests could fail with an error under certain conditions.

This issue could only occur when a chunked request body was split across multiple receives in a very specific pattern, so most users would never encounter it. If it did occur during a load command, the load would only be partially completed and would need to be re-executed.

No index corruption occurs due to this bug.

Fixed a bug that caused a crash due to using the wrong free function#

Fixed a bug where grn_obj_unlink() was used instead of GRN_OBJ_FIN() for bulk objects. This could cause a crash in some cases.

Reported by Daniel Black

See also: https://jira.mariadb.org/browse/MDEV-39098

Experimental features#

These features are still experimental and unstable. We must not use these features in production.

[Data types] Added support for arrays and objects in JSON type#

The JSON type now supports arrays and objects, including nested ones. All JSON value types are now supported.

Added support for OpenZL compression and decompression for scalar columns and Float32 vector columns#

OpenZL compression and decompression are now supported for scalar columns and Float32 vector columns. OpenZL can achieve better compression ratios than Zstandard.

Examples of compression:

The compression of float32 array results for the following data:

  • The number of array elements is 40,960.

  • The number of records is 10,000.

Results:

  • Compress with OpenZL: 1.3GB

  • Compress with Zstandard: 1.5GB

  • No compress: 1.6GB

Added extractor support#

Extractors are a new type of module in Groonga that extract plain text from structured data before tokenization.

The built-in ExtractorHTML extractor strips HTML tags and decodes HTML entities from a value, leaving only the text content.

Here is an example of using ExtractorHTML with the extract command:

extract \
  --extractors 'ExtractorHTML' \
  --value "<html><body>He&lt;ll&gt;o</body></html>"
[[0,0.0,0.0],{"extracted":"He<ll>o"}]

Thanks#

  • Daniel Black

Release 16.0.0 - 2026-02-09#

This is our annual major release! This release doesn’t have any backward incompatible changes! So you can upgrade Groonga without migrating your existing databases. You can still use your existing databases as-is.

Fixes#

Fixed a bug that causes overflow in the key of TABLE_DAT_KEY tables#

If you set a value of 4096 byte against a key, a TABLE_DAT_KEY table may be broken.