Redis and Querying Values

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日久生厌
日久生厌 2020-12-30 13:21

Redis is conceptually different from traditional SQL databases that I use, and I\'m trying to figure out if it is right for my project... I\'ve been looking around but can\'

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  •  谎友^
    谎友^ (楼主)
    2020-12-30 13:53

    Redis's basic data types do not support multi-conditional queries, full-text search, etc. Therefore, we have modified the Redis source code and transformed Redis into a database that can be used like SQL data through auxiliary indexes.

    Ths project homepage is https://oncedb.com

    OnceDB does not change the data storage structure of Redis. Redis database files can be directly operated in OnceDB and then returned to Redis for use.

    Index search

    Create index

    The performance of full-text search is poor. You can improve the performance by creating indexes. The method is to create ordered lists for the indexed fields, and then perform an intersection query operation on these ordered lists when the conditional query is performed.

    # Create hash data
    hmset article:001 poster dota visit 21 key js
    hmset article:002 poster dota visit 11 key c
    hmset article:003 poster like visit 34 key js
    hmset article:004 poster like visit 44 key c
    

    Then we create indexes for the above fields, the weight score is set to: 202000201, an integer about time, the value is the ID value of article

    # Create indexed
    zadd *article.poster:dota 20200201 001 20200201 002
    zadd *article.poster:like 20200201 003 20200201 004
    zadd *article.key:js 20200201 001 20200201 003
    zadd *article.key:c 20200201 002 20200201 004
    # "visit" using its value as the weight score
    zadd *article.visit 21 001 11 002 34 003 44 004
    

    Query by index

    Find the intersection of the two indexes *article.key:js and *article.poster:dota and store them in the *tmp1 ordered list:

    zinterstore *tmp1 2 *article.key:js *article.poster:dota
    > 1
    

    Then *tmp1 stores the ID set that meets the key = js and poster = dota conditions:

    zrange *tmp1 0 -1
    > 001
    

    You can use the zrangehmget command to print the corresponding HASH value:

    zrangehmget *tmp1 0 -1 article: key poster
    1) 001
    2) 40400402
    3) js
    4) dota
    5) 
    6) 
    

    The result is the same as the direct full-text search key = js and poster = dota

    hsearch article:* key = js poster = dota
    1) article:001
    2) js
    3) dota
    

    Search range

    For example, to search for data with the number of visits between 20 and 30, and key = js, you can achieve it by controlling the weight

    Create a temporary index, only take the weight of *article.visit and the data of key = js

    zinterstore *tmp2 2 *article.key:js *article.visit weights 0 1
    > 2
    

    Take data between 20 and 30

    zrangebyscore *tmp2 20 30
    > 001
    

    You can use zrangehmgetbyscore to print the corresponding hash data:

    zrangehmgetbyscore *tmp2 20 30 article: key visit
    1) 001
    2) 21
    3) js
    4) 21
    5) 
    6) 
    

    The results are consistent with those using full-text search:

    hsearch article:* visit >= 20 visit <= 30 key = js
    1) article:001
    2) 21
    3) 
    4) js
    

    Because there are two identical fields, visit> = 20 visit <= 30, the search results will only output one, and the repeated fields in the third row will output empty.

    More OnceDB extended instructions can be viewed: Search, query, calculate, and sum instructions in OnceDB

    Automatic indexing

    The creation and maintenance of Redis indexes is not very convenient. OnceDB can choose to automatically create auxiliary indexes when data is modified.

    Create index:upsert schema field operator value ...

    Use upsert / insert / update directives and special operators to create indexes automatically:

    The example above can be written as:

    upsert article id @ 001 poster ? dota visit / 21 key ? js
    upsert article id @ 002 poster ? dota visit / 11 key ? c
    upsert article id @ 003 poster ? like visit / 34 key ? js
    upsert article id @ 004 poster ? like visit / 44 key ? c
    

    Operator:

    @: Primary key ?: Group index /: Sort index

    The indexes are automatically created after the operation: *article *article.poster:dota *article.poster:like *article.visit *article.key:js *article.key:c

    Multi-condition index query:find schema from to field operator value ...

    For fields with indexes, you can use the find command to query through the index fields. For example, query: data of key = js and poster = dota. You can use "?" To indicate that these two fields are grouped indexes:

    find article 0 -1 key ? js poster ? dota
    1) 1
    2) article:001
    3) js
    4) dota
    

    1 represents the total amount of data. If it is -1, it means that full-text search is used, and the performance is poor.

    Index range query

    You can add @ to specify an index range and use + to specify which index field to use for the score weight range.

    find article 0@20 -1@30 key ? js visit /+ *
    1) 1
    2) article:001
    3) js
    4) 21
    

    Delete index

    OnceDB does not store index definitions. When deleting, you need to manually indicate which fields contain indexes. You need to specify the field names and index operators.

    remove article @ 001 key ? poster ? visit /
    

    You can also customize the index name and weight score. For more instructions, please see: OnceDB data modification and query help documentation

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