Note
The suggest feature specification isn't stable. The specification may be changed.
suggest - returns completion, correction and/or suggestion for a query.
The suggest command returns completion, correction and/or suggestion for a specified query.
See Introduction about completion, correction and suggestion.
suggest types table column query [sortby [output_columns [offset [limit [frequency_threshold [conditional_probability_threshold [prefix_search]]]]]]]
Here are learned data for completion.
Execution example:
load --table event_query --each 'suggest_preparer(_id, type, item, sequence, time, pair_query)'
[
{"sequence": "1", "time": 1312950803.86057, "item": "e"},
{"sequence": "1", "time": 1312950803.96857, "item": "en"},
{"sequence": "1", "time": 1312950804.26057, "item": "eng"},
{"sequence": "1", "time": 1312950804.56057, "item": "engi"},
{"sequence": "1", "time": 1312950804.76057, "item": "engin"},
{"sequence": "1", "time": 1312950805.86057, "item": "engine", "type": "submit"}
]
# [[0, 1337566253.89858, 0.000355720520019531], 6]
Here are learned data for correction.
Execution example:
load --table event_query --each 'suggest_preparer(_id, type, item, sequence, time, pair_query)'
[
{"sequence": "2", "time": 1312950803.86057, "item": "s"},
{"sequence": "2", "time": 1312950803.96857, "item": "sa"},
{"sequence": "2", "time": 1312950804.26057, "item": "sae"},
{"sequence": "2", "time": 1312950804.56057, "item": "saer"},
{"sequence": "2", "time": 1312950804.76057, "item": "saerc"},
{"sequence": "2", "time": 1312950805.76057, "item": "saerch", "type": "submit"},
{"sequence": "2", "time": 1312950809.76057, "item": "serch"},
{"sequence": "2", "time": 1312950810.86057, "item": "search", "type": "submit"}
]
# [[0, 1337566253.89858, 0.000355720520019531], 8]
Here are learned data for suggestion.
Execution example:
load --table event_query --each 'suggest_preparer(_id, type, item, sequence, time, pair_query)'
[
{"sequence": "3", "time": 1312950803.86057, "item": "search engine", "type": "submit"},
{"sequence": "3", "time": 1312950808.86057, "item": "web search realtime", "type": "submit"}
]
# [[0, 1337566253.89858, 0.000355720520019531], 2]
Here is a completion example.
Execution example:
suggest --table item_query --column kana --types complete --frequency_threshold 1 --query en
# [
# [
# 0,
# 1337566253.89858,
# 0.000355720520019531
# ],
# {
# "complete": [
# [
# 1
# ],
# [
# [
# "_key",
# "ShortText"
# ],
# [
# "_score",
# "Int32"
# ]
# ],
# [
# "engine",
# 1
# ]
# ]
# }
# ]
Here is a correction example.
Execution example:
suggest --table item_query --column kana --types correct --frequency_threshold 1 --query saerch
# [
# [
# 0,
# 1337566253.89858,
# 0.000355720520019531
# ],
# {
# "correct": [
# [
# 1
# ],
# [
# [
# "_key",
# "ShortText"
# ],
# [
# "_score",
# "Int32"
# ]
# ],
# [
# "search",
# 1
# ]
# ]
# }
# ]
Here is a suggestion example.
Execution example:
suggest --table item_query --column kana --types suggest --frequency_threshold 1 --query search
# [
# [
# 0,
# 1337566253.89858,
# 0.000355720520019531
# ],
# {
# "suggest": [
# [
# 2
# ],
# [
# [
# "_key",
# "ShortText"
# ],
# [
# "_score",
# "Int32"
# ]
# ],
# [
# "search engine",
# 1
# ],
# [
# "web search realtime",
# 1
# ]
# ]
# }
# ]
Here is a mixed example.
Execution example:
suggest --table item_query --column kana --types complete|correct|suggest --frequency_threshold 1 --query search
# [
# [
# 0,
# 1337566253.89858,
# 0.000355720520019531
# ],
# {
# "suggest": [
# [
# 2
# ],
# [
# [
# "_key",
# "ShortText"
# ],
# [
# "_score",
# "Int32"
# ]
# ],
# [
# "search engine",
# 1
# ],
# [
# "web search realtime",
# 1
# ]
# ],
# "complete": [
# [
# 2
# ],
# [
# [
# "_key",
# "ShortText"
# ],
# [
# "_score",
# "Int32"
# ]
# ],
# [
# "search",
# 2
# ],
# [
# "search engine",
# 2
# ]
# ],
# "correct": [
# [
# 1
# ],
# [
# [
# "_key",
# "ShortText"
# ],
# [
# "_score",
# "Int32"
# ]
# ],
# [
# "search",
# 2
# ]
# ]
# }
# ]
Specifies what types are returned by the suggest command.
Here are available types:
- complete
- The suggest command does completion.
- correct
- The suggest command does correction.
- suggest
- The suggest command does suggestion.
You can specify one or more types separated by |. Here are examples:
It returns correction:
correctIt returns correction and suggestion:
correct|suggestIt returns complete, correction and suggestion:
complete|correct|suggest
Specifies table name that has item_${DATA_SET_NAME} format. For example, item_query is a table name if you created dataset by the following command:
groonga-suggest-create-dataset /tmp/db-path query
Specifies sort key.
Specifies output columns.
Specifies returned records offset.
Specifies number of returned records.
Specifies threshold for item frequency. Returned records must have _score that is greater than or equal to frequency_threshold.
conditional_probability_threshold
Specifies threshold for conditional probability. Conditional probability is used for learned data. It is probability of query submission when query is occurred. Returned records must have conditional probability that is greater than or equal to conditional_probability_threshold.
- Default:
- 0.2
Specifies whether optional prefix search is used or not in completion.
Here are available values:
- yes
- Prefix search is always used.
- no
- Prefix search is never used.
- auto
- Prefix search is used only when other search can't find any records.
Specifies whether optional similar search is used or not in correction.
Here are available values:
- yes
- Similar search is always used.
- no
- Similar search is never used.
- auto
- Similar search is used only when other search can't find any records.
Here is a returned JSON format:
{"type1": [["candidate1", score of candidate1],
["candidate2", score of candidate2],
...],
"type2": [["candidate1", score of candidate1],
["candidate2", score of candidate2],
...],
...}
type
A type specified by types.
candidate
A candidate for completion, correction or suggestion.
score of candidate
A score of corresponding candidate. It means that higher score candidate is more likely candidate for completion, correction or suggestion. Returned candidates are sorted by score of candidate descending by default.