2017-04-19 08:36:11 -04:00
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[[index-modules-index-sorting]]
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== Index Sorting
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2017-07-18 08:06:22 -04:00
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beta[]
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2017-04-19 08:36:11 -04:00
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When creating a new index in elasticsearch it is possible to configure how the Segments
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inside each Shard will be sorted. By default Lucene does not apply any sort.
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The `index.sort.*` settings define which fields should be used to sort the documents inside each Segment.
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[WARNING]
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nested fields are not compatible with index sorting because they rely on the assumption
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that nested documents are stored in contiguous doc ids, which can be broken by index sorting.
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An error will be thrown if index sorting is activated on an index that contains nested fields.
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For instance the following example shows how to define a sort on a single field:
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[source,js]
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--------------------------------------------------
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PUT twitter
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{
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"settings" : {
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"index" : {
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"sort.field" : "date", <1>
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"sort.order" : "desc" <2>
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}
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},
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"mappings": {
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"tweet": {
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"properties": {
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"date": {
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"type": "date"
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}
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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<1> This index is sorted by the `date` field
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<2> ... in descending order.
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It is also possible to sort the index by more than one field:
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[source,js]
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--------------------------------------------------
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PUT twitter
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{
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"settings" : {
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"index" : {
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"sort.field" : ["username", "date"], <1>
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"sort.order" : ["asc", "desc"] <2>
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}
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},
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"mappings": {
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"tweet": {
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"properties": {
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"username": {
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"type": "keyword",
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"doc_values": true
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},
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"date": {
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"type": "date"
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}
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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<1> This index is sorted by `username` first then by `date`
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<2> ... in ascending order for the `username` field and in descending order for the `date` field.
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Index sorting supports the following settings:
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`index.sort.field`::
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The list of fields used to sort the index.
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Only `boolean`, `numeric`, `date` and `keyword` fields with `doc_values` are allowed here.
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`index.sort.order`::
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The sort order to use for each field.
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The order option can have the following values:
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* `asc`: For ascending order
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* `desc`: For descending order.
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`index.sort.mode`::
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Elasticsearch supports sorting by multi-valued fields.
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The mode option controls what value is picked to sort the document.
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The mode option can have the following values:
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* `min`: Pick the lowest value.
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* `max`: Pick the highest value.
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`index.sort.missing`::
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The missing parameter specifies how docs which are missing the field should be treated.
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The missing value can have the following values:
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* `_last`: Documents without value for the field are sorted last.
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* `_first`: Documents without value for the field are sorted first.
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[WARNING]
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Index sorting can be defined only once at index creation. It is not allowed to add or update
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2017-06-08 06:10:46 -04:00
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a sort on an existing index. Index sorting also has a cost in terms of indexing throughput since
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documents must be sorted at flush and merge time. You should test the impact on your application
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before activating this feature.
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2017-06-01 11:23:22 -04:00
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2017-06-08 06:10:46 -04:00
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[float]
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[[early-terminate]]
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=== Early termination of search request
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By default in elasticsearch a search request must visit every document that match a query to
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retrieve the top documents sorted by a specified sort.
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Though when the index sort and the search sort are the same it is possible to limit
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the number of documents that should be visited per segment to retrieve the N top ranked documents globally.
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For example, let's say we have an index that contains events sorted by a timestamp field:
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[source,js]
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--------------------------------------------------
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PUT events
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{
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"settings" : {
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"index" : {
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"sort.field" : "timestamp",
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2017-06-08 19:40:53 -04:00
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"sort.order" : "desc" <1>
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2017-06-08 06:10:46 -04:00
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}
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},
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"mappings": {
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"doc": {
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"properties": {
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"timestamp": {
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"type": "date"
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}
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}
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}
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}
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}
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--------------------------------------------------
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// CONSOLE
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<1> This index is sorted by timestamp in descending order (most recent first)
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You can search for the last 10 events with:
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[source,js]
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--------------------------------------------------
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GET /events/_search
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{
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"size": 10,
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"sort": [
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{ "timestamp": "desc" }
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]
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[continued]
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Elasticsearch will detect that the top docs of each segment are already sorted in the index
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and will only compare the first N documents per segment.
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The rest of the documents matching the query are collected to count the total number of results
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and to build aggregations.
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If you're only looking for the last 10 events and have no interest in
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the total number of documents that match the query you can set `track_total_hits`
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to false:
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[source,js]
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--------------------------------------------------
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GET /events/_search
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{
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"size": 10,
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2017-06-08 19:40:53 -04:00
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"sort": [ <1>
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2017-06-08 06:10:46 -04:00
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{ "timestamp": "desc" }
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],
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"track_total_hits": false
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}
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--------------------------------------------------
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// CONSOLE
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// TEST[continued]
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<1> The index sort will be used to rank the top documents and each segment will early terminate the collection after the first 10 matches.
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This time, Elasticsearch will not try to count the number of documents and will be able to terminate the query
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as soon as N documents have been collected per segment.
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[source,js]
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--------------------------------------------------
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{
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"_shards": ...
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"hits" : {
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"total" : -1, <1>
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"max_score" : null,
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"hits" : []
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},
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"took": 20,
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"timed_out": false
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}
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--------------------------------------------------
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// TESTRESPONSE[s/"_shards": \.\.\./"_shards": "$body._shards",/]
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// TESTRESPONSE[s/"took": 20,/"took": "$body.took",/]
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<1> The total number of hits matching the query is unknown because of early termination.
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NOTE: Aggregations will collect all documents that match the query regardless of the value of `track_total_hits`
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2017-06-01 11:23:22 -04:00
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[[index-modules-index-sorting-conjunctions]]
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=== Use index sorting to speed up conjunctions
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Index sorting can be useful in order to organize Lucene doc ids (not to be
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conflated with `_id`) in a way that makes conjunctions (a AND b AND ...) more
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efficient. In order to be efficient, conjunctions rely on the fact that if any
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clause does not match, then the entire conjunction does not match. By using
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index sorting, we can put documents that do not match together, which will
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help skip efficiently over large ranges of doc IDs that do not match the
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conjunction.
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This trick only works with low-cardinality fields. A rule of thumb is that
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you should sort first on fields that both have a low cardinality and are
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frequently used for filtering. The sort order (`asc` or `desc`) does not
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matter as we only care about putting values that would match the same clauses
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close to each other.
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For instance if you were indexing cars for sale, it might be interesting to
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sort by fuel type, body type, make, year of registration and finally mileage.
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