redis series
- redis publish and subscribe function
- redis message queue
- pipeline of redis
- scan operation of redis
sequence
There are a large number of keys in the redis db or a certain set, zset, hash in the db If there are a lot of elements in it, using the ordinary get all operation is likely to cause redis to be blocked due to this operation, resulting in the inability to respond to other operations. Especially in the context of high concurrency and massive data, this problem is particularly serious. So can it have a paging function like a database? The answer is the scan operation. This article mainly shows how to use it in redis-cli and SpringDataRedis. [Recommendation: redis video tutorial]
scan syntax
After scanning, two parts are returned. The first part is the parameters of the next scan, and the second part is the items that come out of the scan.
Action objects (db, set, zset, hash)
- db(
key
)
127.0.0.1:6379> scan 0 1) "120" 2) 1) "articleMap:63" 2) "articleMap:37" 3) "counter:__rand_int__" 4) "articleMap:60" 5) "tagSet:tag5" 6) "articleMap:80" 7) "messageCache~keys" 8) "mymap" 9) "articleMap:46" 10) "articleMap:55" 127.0.0.1:6379> scan 120 1) "28" 2) 1) "articleMap:17" 2) "tagSet:tag1" 3) "articleMap:18" 4) "articleMap:81" 5) "\xac\xed\x00\x05t\x00\btest-cas" 6) "articleMap:51" 7) "articleMap:94" 8) "articleMap:26" 9) "articleMap:71" 10) "user-abcde"
- set (
value
)
127.0.0.1:6379> sscan myset 0 1) "3" 2) 1) "m" 2) "j" 3) "c" 4) "h" 5) "f" 6) "i" 7) "a" 8) "g" 9) "n" 10) "e" 11) "b" 127.0.0.1:6379> sscan myset 3 1) "0" 2) 1) "l" 2) "k" 3) "d"
- zset(
value & score
)
127.0.0.1:6379> zscan sortset 0 1) "0" 2) 1) "tom" 2) "89" 3) "jim" 4) "90" 5) "david" 6) "100"
- hash(
key & value
)
127.0.0.1:6379> hscan mymap 0 1) "0" 2) 1) "name" 2) "codecraft" 3) "email" 4) "pt@g.cn" 5) "age" 6) "20" 7) "desc" 8) "hello" 9) "sex" 10) "male"
Extra parameters of SCAN
- count(
Specify how many records to take each time
)
127.0.0.1:6379> scan 0 count 5 1) "240" 2) 1) "articleMap:63" 2) "articleMap:37" 3) "counter:__rand_int__" 4) "articleMap:60" 5) "tagSet:tag5"
- match(
match key
)
127.0.0.1:6379> scan 0 match article* 1) "120" 2) 1) "articleMap:63" 2) "articleMap:37" 3) "articleMap:60" 4) "articleMap:80" 5) "articleMap:46" 6) "articleMap:55"
RedisTemplate operation
Traverse the database key
@Test public void scanDbKeys(){ template.execute(new RedisCallback<Iterable<byte[]>>() { @Override public Iterable<byte[]> doInRedis(RedisConnection connection) throws DataAccessException { List<byte[]> binaryKeys = new ArrayList<byte[]>(); Cursor<byte[]> cursor = connection.scan(ScanOptions.scanOptions().count(5).build()); while (cursor.hasNext()) { byte[] key = cursor.next(); binaryKeys.add(key); System.out.println(new String(key, StandardCharsets.UTF_8)); } try { cursor.close(); } catch (IOException e) { // do something meaningful } return binaryKeys; } }); }
Traverse set
/** * sadd myset a b c d e f g h i j k l m n */ @Test public void scanSet(){ Cursor<String> cursor = template.opsForSet().scan("myset",ScanOptions.NONE); while (cursor.hasNext()){ System.out.println(cursor.next()); } }
Traverse zset
/** * zadd sortset 89 tom 90 jim 100 david */ @Test public void scanZSet(){ Cursor<ZSetOperations.TypedTuple<String>> cursor = template.opsForZSet().scan("sortset",ScanOptions.NONE); while (cursor.hasNext()){ ZSetOperations.TypedTuple<String> item = cursor.next(); System.out.println(item.getValue() + ":" + item.getScore()); } }
Traverse hash
/** * hset mymap name "codecraft" * hset mymap email "pt@g.cn" * hset mymap age 20 * hset mymap desc "hello" * hset mymap sex "male" */ @Test public void scanHash(){ Cursor<Map.Entry<Object, Object>> curosr = template.opsForHash().scan("mymap", ScanOptions.NONE); while(curosr.hasNext()){ Map.Entry<Object, Object> entry = curosr.next(); System.out.println(entry.getKey()+":"+entry.getValue()); } }