Groonga 11.0.1 has been released
Groonga 11.0.1 has been released!
How to install: Install
Changes
Here are important changes in this release:
Improvements
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Debian GNU/Linux Added support for a ARM64 package.
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select Added support for customizing adjust weight every key word.
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We need to specify
<or>to all keywords to adjust scores until now. Because the default adjustment of weight (6 or 4) is larger than the default score (1).- Therefore, for example, "A"'s weight is 1 and "B"'s weight is 4 in
A <B. Decremented "B"'s weight (4) is larger than not decremented "A"'s weight (1). This is not works as expected. we need to specify>A <Bto use smaller weight than "A" for "B". "A"'s weight is 6 and "B"'s weight is 4 in>A <B.
- Therefore, for example, "A"'s weight is 1 and "B"'s weight is 4 in
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We can customize adjustment of weight every key word by only specifying
<${WEIGHT}or>${WEIGHT}to target keywords since this release. For example, "A"'s weight is 1 and "B"'s weight is 0.9 inA <0.1B("B"'s weight decrement 0.1). -
However, note that these forms (
>${WEIGHT}...,<${WEIGHT}..., and~${WEIGHT}...) are incompatible.
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select Added support for outputting
FloatandFloat32value in Apache Arrow format. -
select Added support for getting a reference destination data via index column when we output a result.
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Until now, Groonga had returned involuntary value when we specified output value like
index_column.xxx. For example, A value of--columns[tags].value purchases.tagwas["apple",["many"]],["banana",["man"]],["cacao",["man"]]in the following example. In this case, the expected values was["apple",["man","many"]],["banana",["man"]],["cacao",["woman"]]. In this release, we can get a correct reference destination data via index column as below.table_create Products TABLE_PAT_KEY ShortText table_create Purchases TABLE_NO_KEY column_create Purchases product COLUMN_SCALAR Products column_create Purchases tag COLUMN_SCALAR ShortText column_create Products purchases COLUMN_INDEX Purchases product load --table Products [ {"_key": "apple"}, {"_key": "banana"}, {"_key": "cacao"} ] load --table Purchases [ {"product": "apple", "tag": "man"}, {"product": "banana", "tag": "man"}, {"product": "cacao", "tag": "woman"}, {"product": "apple", "tag": "many"} ] select Products \ --columns[tags].stage output \ --columns[tags].flags COLUMN_VECTOR \ --columns[tags].type ShortText \ --columns[tags].value purchases.tag \ --output_columns _key,tags [ [ 0, 0.0, 0.0 ], [ [ [ 3 ], [ [ "_key", "ShortText" ], [ "tags", "ShortText" ] ], [ "apple", [ "man", "many" ] ], [ "banana", [ "man" ] ], [ "cacao", [ "woman" ] ] ] ] ]
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select Added support for specifying index column directly as a part of nested index.
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We can search source table after filtering by using
index_column.except_source_column. For example, we specifycomments.contentwhen searching in the following example. In this case, at first, this query execute full text search fromcontentcolumn ofCommenttstable, then fetch the records of Articles table which refers to already searched records of Comments table.table_create Articles TABLE_HASH_KEY ShortText table_create Comments TABLE_NO_KEY column_create Comments article COLUMN_SCALAR Articles column_create Comments content COLUMN_SCALAR ShortText column_create Articles content COLUMN_SCALAR Text column_create Articles comments COLUMN_INDEX Comments article table_create Terms TABLE_PAT_KEY ShortText \ --default_tokenizer TokenBigram \ --normalizer NormalizerNFKC130 column_create Terms articles_content COLUMN_INDEX|WITH_POSITION \ Articles content column_create Terms comments_content COLUMN_INDEX|WITH_POSITION \ Comments content load --table Articles [ {"_key": "article-1", "content": "Groonga is fast!"}, {"_key": "article-2", "content": "Groonga is useful!"}, {"_key": "article-3", "content": "Mroonga is fast!"} ] load --table Comments [ {"article": "article-1", "content": "I'm using Groonga too!"}, {"article": "article-3", "content": "I'm using Mroonga!"}, {"article": "article-1", "content": "I'm using PGroonga!"} ] select Articles --match_columns comments.content --query groonga \ --output_columns "_key, _score, comments.content [ [ 0, 0.0, 0.0 ], [ [ [ 1 ], [ [ "_key", "ShortText" ], [ "_score", "Int32" ], [ "comments.content", "ShortText" ] ], [ "article-1", 1, [ "I'm using Groonga too!", "I'm using PGroonga!" ] ] ] ] ]
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load Added support for loading reference vector with inline object literal.
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For example, we can load data like
"key" : "[ { "key" : "value", ..., "key" : "value" } ]"as below.table_create Purchases TABLE_NO_KEY column_create Purchases item COLUMN_SCALAR ShortText column_create Purchases price COLUMN_SCALAR UInt32 table_create Settlements TABLE_HASH_KEY ShortText column_create Settlements purchases COLUMN_VECTOR Purchases column_create Purchases settlements_purchases COLUMN_INDEX Settlements purchases load --table Settlements [ { "_key": "super market", "purchases": [ {"item": "apple", "price": 100}, {"item": "milk", "price": 200} ] }, { "_key": "shoes shop", "purchases": [ {"item": "sneakers", "price": 3000} ] } ] - It makes easier to add JSON data into reference columns by this feature.
- Currently, this feature only support with JSON input.
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load Added support for loading reference vector from JSON text.
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We can load data to reference vector from source table with JSON text as below.
table_create Purchases TABLE_HASH_KEY ShortText column_create Purchases item COLUMN_SCALAR ShortText column_create Purchases price COLUMN_SCALAR UInt32 table_create Settlements TABLE_HASH_KEY ShortText column_create Settlements purchases COLUMN_VECTOR Purchases column_create Purchases settlements_purchases COLUMN_INDEX Settlements purchases load --table Settlements [ { "_key": "super market", "purchases": "[{\"_key\": \"super market-1\", \"item\": \"apple\", \"price\": 100}, {\"_key\": \"super market-2\", \"item\": \"milk\", \"price\": 200}]" }, { "_key": "shoes shop", "purchases": "[{\"_key\": \"shoes shop-1\", \"item\": \"sneakers\", \"price\": 3000}]" } ] dump \ --dump_plugins no \ --dump_schema no load --table Purchases [ ["_key","item","price"], ["super market-1","apple",100], ["super market-2","milk",200], ["shoes shop-1","sneakers",3000] ] load --table Settlements [ ["_key","purchases"], ["super market",["super market-1","super market-2"]], ["shoes shop",["shoes shop-1"]] ] column_create Purchases settlements_purchases COLUMN_INDEX Settlements purchases -
Currently, this feature doesn't support nested reference record.
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[Windows] Added support for UNIX epoch for
time_classify_*functions. -
query_parallel_or Added a new function for processing queries in parallel.
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select Added support for ignoring nonexistent sort keys.
- Groonga had been outputted error when we specified nonexistent sort keys until now. However, Groonga ignore nonexistent sort keys since this release. (Groonga doesn't output error.)
- This feature implements for consistency.
Because we just ignore invalid values in
output_columnsand most of invalid values insort_keys.
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select Added support for ignoring nonexistent tables in
drilldowns[].table.- Groonga had been outputted error when we specified nonexistent tables in
drilldowns[].tableuntil now. However, Groonga ignore nonexistent tables indrilldowns[].tablesince this release. (Groonga doesn't output error.) - This feature implements for consistency.
Because we just ignore invalid values in
output_columnsand most of invalid values insort_keys.
- Groonga had been outputted error when we specified nonexistent tables in
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[httpd] Updated bundled nginx to 1.19.8.
Fixes
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reference_acquire Fixed a bug that Groonga crash when a table's reference is acquired and a column is added to the table before auto release is happened.
- Because the added column's reference isn't acquired but it's released on auto release.
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[Windows] Fixed a bug that one or more processes fail an output backtrace on SEGV when a new backtrace logging process starts when another backtrace logging process is running in another thread.
Known Issues
- Currently, Groonga has a bug that there is possible that data is corrupt when we execute many additions, delete, and update data to vector column.
Conclusion
Please refert to the following news for more details.
Let's search by Groonga!