Mixing
Redis using too much memory smaller number of keys
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I have a redis standalone server, with around 8000 keys at a given instance .
The used_memeory is showing to be around 8.5 GB.
My individuals key-value size is max around 50kb , by that calculation the used_memory should be less than 1 GB (50kb * 8000)
I am using spring RedisTemplate with default pool configuration to connect to redis
Any idea what should I look into, to narrow down where the memory is being consumed ?
redis
asked Jan 3 at 14:55
Manas SaxenaManas Saxena
4942822
add a comment |
I have a redis standalone server, with around 8000 keys at a given instance .
The used_memeory is showing to be around 8.5 GB.
My individuals key-value size is max around 50kb , by that calculation the used_memory should be less than 1 GB (50kb * 8000)
I am using spring RedisTemplate with default pool configuration to connect to redis
Any idea what should I look into, to narrow down where the memory is being consumed ?
redis
asked Jan 3 at 14:55
Manas SaxenaManas Saxena
4942822
What is data storage type for your case i.e. are you using normal key-value or hierarchical data type
– swayamraina
Jan 4 at 9:31
I am using zset
– Manas Saxena
Jan 4 at 9:34
add a comment |
I have a redis standalone server, with around 8000 keys at a given instance .
The used_memeory is showing to be around 8.5 GB.
My individuals key-value size is max around 50kb , by that calculation the used_memory should be less than 1 GB (50kb * 8000)
I am using spring RedisTemplate with default pool configuration to connect to redis
Any idea what should I look into, to narrow down where the memory is being consumed ?
redis
asked Jan 3 at 14:55
Manas SaxenaManas Saxena
4942822
I have a redis standalone server, with around 8000 keys at a given instance .
The used_memeory is showing to be around 8.5 GB.
My individuals key-value size is max around 50kb , by that calculation the used_memory should be less than 1 GB (50kb * 8000)
I am using spring RedisTemplate with default pool configuration to connect to redis
Any idea what should I look into, to narrow down where the memory is being consumed ?
redis
redis
asked Jan 3 at 14:55
Manas SaxenaManas Saxena
4942822
asked Jan 3 at 14:55
Manas SaxenaManas Saxena
4942822
asked Jan 3 at 14:55
Manas SaxenaManas Saxena
4942822
asked Jan 3 at 14:55
Manas SaxenaManas Saxena
4942822
asked Jan 3 at 14:55
Manas SaxenaManas Saxena
4942822
4942822
What is data storage type for your case i.e. are you using normal key-value or hierarchical data type
– swayamraina
Jan 4 at 9:31
I am using zset
– Manas Saxena
Jan 4 at 9:34
add a comment |
What is data storage type for your case i.e. are you using normal key-value or hierarchical data type
– swayamraina
Jan 4 at 9:31
I am using zset
– Manas Saxena
Jan 4 at 9:34
What is data storage type for your case i.e. are you using normal key-value or hierarchical data type
– swayamraina
Jan 4 at 9:31
What is data storage type for your case i.e. are you using normal key-value or hierarchical data type
– swayamraina
Jan 4 at 9:31
I am using zset
– Manas Saxena
Jan 4 at 9:34
I am using zset
– Manas Saxena
Jan 4 at 9:34
add a comment |
1 Answer
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zset internally uses two data structures to hold the same elements in order to get O(log(N)) INSERT and REMOVE operations into a sorted data structure.
The two Data-structures to be specific are,
- Hash Table
- Skip list
Storage for ideal cases according to my research is in the following order, hset < set < zset
I would recommend you to start using hset in case you have hierarchical data storage. This would lower down your memory consumption but might make searching teeny-tiny bit slower (only if one key has more than say a couple of hundred records)
answered Jan 4 at 10:17
swayamrainaswayamraina
875813
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
zset internally uses two data structures to hold the same elements in order to get O(log(N)) INSERT and REMOVE operations into a sorted data structure.
The two Data-structures to be specific are,
- Hash Table
- Skip list
Storage for ideal cases according to my research is in the following order, hset < set < zset
I would recommend you to start using hset in case you have hierarchical data storage. This would lower down your memory consumption but might make searching teeny-tiny bit slower (only if one key has more than say a couple of hundred records)
answered Jan 4 at 10:17
swayamrainaswayamraina
875813
add a comment |
zset internally uses two data structures to hold the same elements in order to get O(log(N)) INSERT and REMOVE operations into a sorted data structure.
The two Data-structures to be specific are,
- Hash Table
- Skip list
Storage for ideal cases according to my research is in the following order, hset < set < zset
I would recommend you to start using hset in case you have hierarchical data storage. This would lower down your memory consumption but might make searching teeny-tiny bit slower (only if one key has more than say a couple of hundred records)
answered Jan 4 at 10:17
swayamrainaswayamraina
875813
add a comment |
zset internally uses two data structures to hold the same elements in order to get O(log(N)) INSERT and REMOVE operations into a sorted data structure.
The two Data-structures to be specific are,
- Hash Table
- Skip list
Storage for ideal cases according to my research is in the following order, hset < set < zset
I would recommend you to start using hset in case you have hierarchical data storage. This would lower down your memory consumption but might make searching teeny-tiny bit slower (only if one key has more than say a couple of hundred records)
answered Jan 4 at 10:17
swayamrainaswayamraina
875813
zset internally uses two data structures to hold the same elements in order to get O(log(N)) INSERT and REMOVE operations into a sorted data structure.
The two Data-structures to be specific are,
- Hash Table
- Skip list
Storage for ideal cases according to my research is in the following order, hset < set < zset
I would recommend you to start using hset in case you have hierarchical data storage. This would lower down your memory consumption but might make searching teeny-tiny bit slower (only if one key has more than say a couple of hundred records)
answered Jan 4 at 10:17
swayamrainaswayamraina
875813
edited Jan 4 at 10:26
answered Jan 4 at 10:17
swayamrainaswayamraina
875813
answered Jan 4 at 10:17
swayamrainaswayamraina
875813
answered Jan 4 at 10:17
swayamrainaswayamraina
875813
875813
add a comment |
add a comment |
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What is data storage type for your case i.e. are you using normal key-value or hierarchical data type
– swayamraina
Jan 4 at 9:31
I am using zset
– Manas Saxena
Jan 4 at 9:34