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chore: remove repetitive words
Signed-off-by: shuangcui <fliter@qq.com>
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parent
0b7bebeeb6
commit
5c95b5c933
@ -530,7 +530,7 @@ pub fn perform_search(
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// The attributes to retrieve are the ones explicitly marked as to retrieve (all by default),
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// The attributes to retrieve are the ones explicitly marked as to retrieve (all by default),
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// but these attributes must be also be present
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// but these attributes must be also be present
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// - in the fields_ids_map
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// - in the fields_ids_map
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// - in the the displayed attributes
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// - in the displayed attributes
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let to_retrieve_ids: BTreeSet<_> = query
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let to_retrieve_ids: BTreeSet<_> = query
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.attributes_to_retrieve
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.attributes_to_retrieve
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.as_ref()
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.as_ref()
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@ -168,7 +168,7 @@ impl<'t, 'b, 'bitmap> FacetRangeSearch<'t, 'b, 'bitmap> {
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}
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}
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// should we stop?
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// should we stop?
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// We should if the the search range doesn't include any
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// We should if the search range doesn't include any
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// element from the previous key or its successors
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// element from the previous key or its successors
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let should_stop = {
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let should_stop = {
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match self.right {
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match self.right {
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@ -232,7 +232,7 @@ impl<'t, 'b, 'bitmap> FacetRangeSearch<'t, 'b, 'bitmap> {
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}
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}
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// should we stop?
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// should we stop?
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// We should if the the search range doesn't include any
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// We should if the search range doesn't include any
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// element from the previous key or its successors
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// element from the previous key or its successors
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let should_stop = {
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let should_stop = {
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match self.right {
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match self.right {
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@ -5,7 +5,7 @@ The typo ranking rule should transform the query graph such that it only contain
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the combinations of word derivations that it used to compute its bucket.
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the combinations of word derivations that it used to compute its bucket.
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The proximity ranking rule should then look for proximities only between those specific derivations.
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The proximity ranking rule should then look for proximities only between those specific derivations.
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For example, given the the search query `beautiful summer` and the dataset:
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For example, given the search query `beautiful summer` and the dataset:
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```text
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```text
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{ "id": 0, "text": "beautigul summer...... beautiful day in the summer" }
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{ "id": 0, "text": "beautigul summer...... beautiful day in the summer" }
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{ "id": 1, "text": "beautiful summer" }
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{ "id": 1, "text": "beautiful summer" }
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