I am looking for a way to install keyring_aws plugin in mysql community edition. Is it possible? I gone through couple of docs, > https://dev.mysql.com/doc/refman/5.7/en/keyring-aws-plugin.html > https://dev.mysql.com/doc/refman/5.7/en/keyring-installation.html And also tried to findout keyring_aws.so file, but couldn't find it anywhere. I checked in mysql dir also. root@server:~# ls -l /usr/lib/mysql/plugin/ total 644 -rw-r--r-- 1 root root 21224 Jan 22 17:26 adt_null.so -rw-r--r-- 1 root root 6288 Jan 22 17:26 auth_socket.so -rw-r--r-- 1 root root 44144 Jan 22 17:26 connection_control.so -rw-r--r-- 1 root root 108696 Jan 22 17:26 innodb_engine.so -rw-r--r-- 1 root root 88608 Jan 22 17:26 keyring_file.so -rw-r--r-- 1 root root 154592 Jan 22 17:26 libmemcached.so -rw-r--r-- 1 root root 9848 Jan 22 17:26 locking_service.so -rw-r--r-- 1 root root 10840 Jan 22 17:26 mypluglib.so -rw-r--r-- 1 root root 6288 Jan 22 17:26 mysql_no_login.so -rw-r--r-- 1 root root 56064 Jan 22 17:26 rewriter.so -rw-r--r-- 1 root root 56936 Jan 22 17:26 semisync_master.so -rw-r--r-- 1 root root 14768 Jan 22 17:26 semisync_slave.so -rw-r--r-- 1 root root 27568 Jan 22 17:26 validate_password.so -rw-r--r-- 1 root root 31296 Jan 22 17:26 version_token.so Can we build this .so file from scratch? If yes, where can I find the source?

I'm working on archiving a bunch of tables in an environment where archiving was never done, with some data going back 10 years. I've written a script to perform the work, which loops through the primary key (an autoincrement bigint) *n* rows at a time, calling a procedure to archive the data to a separate table and then deleting that same data from the main table. I'm doing it in small batches to prevent any long term locking of the main tables. It also sleeps in between each loop iteration. Batch size and sleep time are configurable via a config file. On my test system, for this table, I'm using a batch size of 1000 and a sleep time of 0. Instance class is r7g.4xl. Most tables archive at several thousand rows per second, which is acceptable. But I have one table whose archiving is going very slowly; averaging under 550 rows/sec. There is no other activity in the database (there are other archives running against other DBs in the cluster at the same time, but killing them didn't improve the performance of this one). Here's the table schema (the schema for the archive table is identical):

CREATE TABLE inbox_item (
  id bigint NOT NULL AUTO_INCREMENT,
  user_id bigint NOT NULL,
  template_id bigint NOT NULL,
  url varchar(4000) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL,
  created_at datetime NOT NULL,
  hash varchar(128) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL,
  parameters varchar(4000) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci DEFAULT NULL,
  PRIMARY KEY (id),
  UNIQUE KEY hash_uidx (hash),
  KEY template_id_idx (template_id),
  KEY user_id_created_at_idx (user_id,created_at)
) ENGINE=InnoDB AUTO_INCREMENT=442872663 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci

Note that while there are two large varchars, total actual data width is under 300 bytes. Here's the procedure that's being called:

CREATE DEFINER=root@% PROCEDURE archive_inbox_item_proc(IN pkmin bigint, IN pkmax bigint, IN querymax bigint)
begin
        declare exit handler for sqlexception
        begin
                get diagnostics condition 1
                    @err = MYSQL_ERRNO, @msg = MESSAGE_TEXT;
                select -1;
                select concat('Error ', cast(@err as char), ': ',@msg) 'Error';
                rollback;
        end;

        start transaction;
        insert ignore into inbox.inbox_item_archive select arctable.* from inbox.inbox_item as arctable  where created_at = pkmin and arctable.id = pkmin and arctable.id < querymax and arctable.id <= pkmax ;
        select row_count();
        commit;
end

pkmin is always the actual minimum pkey value. There are no foreign keys or triggers referencing the table. Here's the table status:

Name: inbox_item
         Engine: InnoDB
        Version: 10
     Row_format: Dynamic
           Rows: 299879061
 Avg_row_length: 243
    Data_length: 72988737536
Max_data_length: 0
   Index_length: 126937300992
      Data_free: 45770342400
 Auto_increment: 442872663
    Create_time: 2025-03-28 06:15:36
    Update_time: 2025-08-05 18:04:55
     Check_time: NULL
      Collation: utf8mb4_unicode_ci
       Checksum: NULL
 Create_options:
        Comment:

Any ideas on what's causing this to run so slow relative to other tables in other databases?

I saw a solution like this below: 1. create a new table like your source table. 2. alter that new table the way you want. 3. insert your data into the new table. 4. create indexes etc. as needed on the new table. 5. rename your old table to something like ..._old or whatever. 6. rename your new table to the former name of the old one. 7. copy any missing rows from the _old table to the new one. [Reference for an above solution](https://dba.stackexchange.com/questions/6131/mysql-speed-up-execution-of-alter-table) But the above solution might cause data unavailability if there is a huge amount of data added before copying any missing rows from the _old table to the new one. Is there any better solution than this, using AWS DMS, etc? I also want to change the collate of all tables present in the database. Is it possible to get all the data replicated between two RDS DBs continuously, like new data entered in database A gets into Database B and viceversa? Since I have around 50-60GB data any best way to solve this is appreciated. **Update:** - I have around **50-60GB** of data. - Mysql version: **5.7** - I need to change collation on all my tables

for the first time I am faced with such a problem that has puzzled everyone. I have all hosting busy (AWS lightsail) 78GB and after a few analyzes I realized that 90% of the memory is occupied in the mysql/data folder. My wordpress website is weight - 6GB and I removed all binary logs before the problem, so the problem is not connected with that. I can no longer log into *phpmyadmin*, because there is no free space left on the disk. But when I got there until the problem I saw that wp-option has a crazy amount of GB. No plugin was able to clear this and I decided to put it off. Now that everything is busy, most of the commands cannot be executed, especially the mysql commands. I am using SSH. Help if possible.

We are running postgres 14.12 in rds and expirence very slow IO reads.. around 30MB/s on index scans. we can't figure out what might be the cause of it. any ideas to what we should / could check? **configuration** instance class: db.m6idn.8xlarge (which should support 3125MB/s throughput) RAM: 128GB vCPU: 32 storage type: gp3 with 25000 IOPS (we only reach 18K) and 4000MiB/s throughput. most of our slow queries are due to slow IO read..

My Redshift serverless shows massive storage size usage for tiny tables that so far have had only a couple DDL statements, only inserts, and are overall tiny tables. When I run select "schema", "table", "tbl_rows", "size" FROM SVV_TABLE_INFO where "schema" = 'x' and "table = 'y' I get 36 rows with 2580 "size", which according to Redshift docs are 1mb blocks, so 2.6 GB of storage used with 36 rows. The SVV_TABLE_INFO columns empty, unsorted, vacuum_sort_benefit are all 0. The fun part is when I run select * from x.y I can copy the entire resultset to my clipboard and it comes to ~23kb total. The AWS Redshift Serverless Web GUI similarly reports a whopping 1.1 TB of storage used (the same as when running sum("size") against the SVV table btw) in the cluster. There is at most 100gb used in total. Can someone help me figure out how/where those huge storage numbers come from? ## EDIT - Full SVV Dump for one table

{
	"database": "xxx",
	"schema": "x",
	"table_id": 2234810,
	"table": "y",
	"encoded": "Y",
	"diststyle": "KEY(id)",
	"sortkey1": "received_at",
	"max_varchar": 65535,
	"sortkey1_enc": "none",
	"sortkey_num": 1,
	"size": 2580,
	"pct_used": 0.0040,
	"empty": 0,
	"unsorted": 0.00,
	"stats_off": 0.00,
	"tbl_rows": 36,
	"skew_sortkey1": 1.00,
	"skew_rows": 100.00,
	"estimated_visible_rows": 36,
	"risk_event": null,
	"vacuum_sort_benefit": 0.00,
	"create_time": "2024-08-05T07:48:07.454Z"
}

I have a dump of a postgis layer (layer.dump), which I am trying to add to my heroku database (mydatabase). The postgis layer is stored on S3 (https://s3.amazonaws.com/layer.dump) . I would like to add the layer to to the heroku database and previously used heroku pgbackups:restore DATABASE 'https://s3.amazonaws.com/layer.dump '. However, the new heroku pg:backups restore 'https://s3.amazonaws.com/layer.dump ' DATABASE deletes all data from the target database before restoring the backup (https://devcenter.heroku.com/articles/heroku-postgres-backups) . Is there still a way to only restore a single table and leave the remaining tables in the database untouched?

The infrastructure of our system looks like this. An AWS lambda function receives requests such as (accountId, .....). It creates an entry in the MySQL database using a newly generated UUID as caseId. (caseId, accountId, ....). The insert is a conditional insert operation discussed in detail below. I am able to avoid race condition by setting transaction isolation to SERIALIZABLE. However, the issue is that I do not have any control over how many concurrent requests will be successfully processed. For example, consider following concurrent requests.

request  | accountId | field1 | ...  
 1         a1          value1   ....   true     --- create a new entry with caseId Idxxx
 2         a1          value2   ....   false    --- update existing entry with caseId Idxxx 
 3         a1          value3   ....   false    --- update existing entry with caseId Idxxx 
 4         a1          value4   ....   false    --- update existing entry with caseId Idxxx

With our current implementation we are getting CannotAquireLockException. What are the ways in which I can avoid retry failures (CannotAquireLockException) ? The detailed table schema and condition are described below: The database is a mysql database system with the following table schema.

Table1: case table

|caseId(PK) | accountId | status |  .....

Table2: case reopen table

|caseId(FK)| casereopenId(PK)| caseReopenTime|

Table3: Alert table

Id (incrementing id) | alertId | accountId |

The lambda function tries to "create" a case in the database. the create wrapper, generates a UUID for caseId. The goal is : - check if an accountId already exists in case table. - if it does, then - check if status is OPEN - get the caseId for the accountId. - check if the caseId is present in case reopen table. - if above condition is false, then add an entry into the case table. Thanks!

We are currently hosting a postgres RDS database and our team is noticing slowup in our querying service. I'm noticing a spike in the metric, CheckpointLag and I've been tasked in trying to find where this occurs specifically on the AWS side of things. In monitoring detailed performance, we've seen that our queries are much below (20%) what our expected average active sessions (AAS) are said to reach. I also monitored the queries individually with EXPLAIN ANALYZE and the most extreme query is takes 0.5s to compute. This leads me to believe there's something else taking too long. After checking other potential metrics, CPU, BurstBalance, etc... all appear normal, there is one metric CheckpointLag which appears to have a spike under use and I can't seem to find documentation on. I can't seem to find what this means and the expected *acceptable* value we should expect with a db.m4.xLarge. With no, to low, usage -- it appears to be ~140 seconds. Under normal, expected usage it jumps to ~400 seconds. I'm asking what this metric really means, if the values are of *expected* or *normal* values, and if there's any other ways I can see if my RDS instance is the cause of my slowup? **EDIT:** Checkpoint lag is defined as a metric here: https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/rds-metrics.html with the description of The amount of time since the most recent checkpoint. It was fairly vague and hard to decipher the true meaning. For my metrics, it appears that its pulling from this already pre-defined metric, but if there's a way to dive deeper in how its querying the instance, please let me know. **Follow-Up** I ended up editing queries to group results and reduce the number of rows being exported at one time as our team was querying way too many rows to begin with. With this, CheckpointLag went down and I associated it with time taken to either reach or perform queries on RDS (duh!), but I still have not pinpointed exact meaning. There must've been some bottleneck in outputting all of the rows and cause the "lag" to rise...

How can I configure AWS services to notify me of failed pg_cron job runs in the cron.job_run_details table using only the AWS Management Console or PostgreSQL settings, without writing any code?

I have an RDS Postgres instance on a t3.small and am trying to drive down the CPU usage of my clients connecting to it (I have a few API services connected). I've stopped all my services connecting to my DB to see how low the CPU usage will go and it does not go below 5% CPU Utilization, even after a reboot (see attached image, right at the end is where I stopped my services and rebooted the DB server). I have ran SELECT * FROM pg_stat_activity and can confirm that there are no clients connected, but there are the usual AWS monitors and other wait_event_type=Activity rows. Does RDS have a number of background services that will keep the CPU Utilization hovering around 5%?

We have multiple databases in a single RDS instance. Because of any reason if we have load in 1 database it stops all the databases. I'm not able to move any of the database because of following reasons: 1. In MySQL triggers we are calling other databases and as they are in a same server it works. 2. What we can written in trigger we can write the same in App Server but it's going to be tedious tasks. 3. I'm not using Aurora so Lambda functions are out of scope for me. So, currently I'm looking for a solution where I can limit the database so even if there were too much db load it should not bring down all the databases. AWS RDS MySQL5.7 Thank you in advance.

I am working with multiple AWS intances connected to the same MongoDB database (inside Compose.io Elastic deployment). But i am getting the error server : sockets closed after a few minutes. Can anyone give me any hint about what may be wrong with the connection code? **CONNECTION CODE** var url = "mongodb://:@:,:/?replicaSet="; var options = { server : {"socketOptions.keepAlive": 1}, replSet : { "replicaSet": , "socketOptions.keepAlive": 1 } }; MongoClient.connect(url, options, function(err, db) { ... }); **ERROR MESSAGE** Potentially unhandled rejection MongoError: server : sockets closed at null. (/var/app/current/node_modules/mongodb/node_modules/mongodb-core/lib/topologies/server.js:328:47) at g (events.js:199:16) at emit (events.js:110:17) at null. (/var/app/current/node_modules/mongodb/node_modules/mongodb-core/lib/connection/pool.js:101:12) at g (events.js:199:16) at emit (events.js:110:17) at Socket. (/var/app/current/node_modules/mongodb/node_modules/mongodb-core/lib/connection/connection.js:142:12) at Socket.g (events.js:199:16) at Socket.emit (events.js:107:17) at TCP.close (net.js:485:12)

I set up an audit in SQL Server that saves audit logs (.sqlaudit files) to RDS, which we then copy over to S3 using a standard process. All of the documentation I can find on reading these audit files uses the following query to read them from RDS: SELECT * FROM msdb.dbo.rds_fn_get_audit_file ('D:\rdsdbdata\SQLAudit\transmitted\*.sqlaudit' ,default,default) RDS has an option setting called RETENTION_TIME for SQL Server Audit which allows you to specify a maximum of 840 hours before the files are removed from the RDS instance. I need to to be able to read the audit files for a longer period of time, so I am looking for a way to query the audit files in S3 instead, where they are retained. One way may be to use sys.fn_get_audit_file, but I cannot do this with any user attached to this server that my organization has access to, even the admin user. None of the users have proper permissions for this and I don't see any way they can be granted. With the .sqlaudit files sitting in the S3 bucket, how could I go about reading the files? Perhaps S3 Select could do it somehow, or maybe there's another obvious solution I'm overlooking?

I got a warning message about running out of AWS RDS local storage. > The free storage capacity for DB Instance: {MY INSTANCE NAME} is low > at 2% of the provisioned storage [Provisioned Storage: 157.36 GB, Free > Storage: 3.35 GB]. You may want to increase the provisioned storage to > address this issue. According to the AWS document, local storage depends on instance type and can be increased by scale up : https://aws.amazon.com/premiumsupport/knowledge-center/aurora-mysql-local-storage/?nc1=h_ls But, I would like to clear the local storage instead of scaling up the instance because only one instance of the read cluster has insufficient local storage. I restarted Aurora instance but the local storage is still almost full. How can I clear local storage? It's MySQL version is 5.6.

I have an RDS instance with Aurora Mysql 5.7.12 and I noticed that there are other versions of Aurora Mysql 5.7, but I don't understand what is the difference between them. Some of the version listed are: - Aurora (MySQL)-5.7.12 <- The one that I have. - Aurora (MySQL 5.7)-2.03.2 - Aurora (MySQL 5.7)-2.03.3 - Aurora (MySQL 5.7)-2.03.4 - Aurora (MySQL 5.7)-2.04.1 - Etc... I attach an image of the AWS Console: I want to chose the right version (the one that have most bug fixes in order to have better stability in my system).

How does Amazon Aurora handle conditional queries based on MySQL version? I was unable to find any documentation on this. For example, the code below inserts into a database for MySQL 5.6.4 or newer. What is result in Aurora? I could spin up an instance but wanted to read the documentation about this to understand what incompatible features there are. /*!50604 REPLACE INTO phppos_app_config (key, value) VALUES ('supports_full_text', '1')*/;

I have a PG 15(.5) RDS instance, which is experiencing intermittent random(?) periods of high cpu; that do not seem to, afaict, correlate with an obvious cause: Here is one example. The queries being made before/during & after are the same; and if run with the same params once the cpu drops back down, are quick as before. I also don't see any increase in transactions: or tuples: during that period; or any large vacuum. The only graph that seems to line up, is this one: according to the pg docs, this is: > Number of times disk blocks were found already in the buffer cache, so that a read was not necessary so I'm not clear why that would be related. The instance is an db.r7g.8xlarge, with 1758 GiB of gp2; and isn't running particularly hot, as the graph shows. Is there something I can do to find out what the cpu is actually doing? Do I need to catch it in the act?

I'm suddenly having intermittent 2003 connection errors and I can't find anything that has changed that can explain it. These servers have been running smoothly for years and suddenly two days ago these errors started showing up in my logs. The application successfully connects to and queries the database almost all the time but sporadically hangs when trying to connect after several queries in quick succession. The connection timeouts always happen at random intervals. It worked just fine before two days ago and the code hasn't changed in 4 years. Things I've tried that didn't work: - Checked all InnoDB tables for corruption - Increased the back_log value in my.cnf from 50 to 1000 (and restarted MySQL) - Increased the max_connections value in my.cnf from 100 to 200 (and restarted MySQL) - Increased net.core.somaxconn from 128 to 1024 - Increased net.ipv4.tcp_max_syn_backlog from 1024 to 8192 - Verified there are no firewall rules blocking or throttling connections - Flushed the MySQL query cache - Cleared the MySQL query cache - Restarted the application server and database server (there are two separate servers) - Asked it nicely to simply start working again My servers are EC2 instances in AWS and nothing about their configuration has been changed. There's no unusual traffic and the CPU, memory, and disk usage are well below 80%. Please help!

I am creating AWS DMS task for migrating data from GCP SQL server to AWS Aurora MySQL. How can I attach log group which I created? I could able to enable cloud watch logs for the task but when I click on "View CloudWatch logs" its showing as log group doesn't exit. Details in image -