According to the MySQL documentation we can truncate the performance_schema with the help of the following call:
CALL sys.ps_truncate_all_tables(FALSE);
Internally this procedure is coded like follows. It actually executes TRUNCATE TABLE statements against a list of tables obtained with the masks '%summary%' and '%history%'.
The problem is that root user isn't able to perform the TRUNCATE TABLE statement on the performance_schema database in Google Cloud SQL due to superuser restrictions.
mysql> truncate table performance_schema.events_statements_summary_by_digest ;
ERROR 1227 (42000): Access denied; you need (at least one of)
the SUPER privilege(s) for this operation
I didn't find any Cloud SQL Admin API or other method to do this.
Any advice, how to reset the MySQL performance_schema in Google Cloud SQL without restarting DB instance.
UPD. I have found that it does not work for MySQL 5.7 but works well for MySQL 8.0 in Google Cloud SQL. So that if you can migrate your Google DB instance to MySQL 8.0 it would be workaround.
Currently there are no workarounds other than restarting the DB instances. And there is already a feature request raised for the same. You can +1 and CC yourself in the request to show interest in this being implemented and receive an email in case there are any updates.
In case you want to use performance_schema for database sql query analysis, as an alternative, you can use CloudSql Query Insights. Query insights helps you detect, diagnose, and prevent query performance problems for Cloud SQL databases. It supports intuitive monitoring and provides diagnostic information that helps you go beyond detection to identify the root cause of performance problems.
Or you can contact Google support, Product Team may offer up the stored procedure solution.
Related
I would like to automatically stream data from an external PostgreSQL database into a Google Cloud Platform BigQuery database in my GCP account. So far, I have seen that one can query external databases (MySQL or PostgreSQL) with the EXTERNAL_QUERY() function, e.g.:
https://cloud.google.com/bigquery/docs/cloud-sql-federated-queries
But for that to work, the database has to be in GCP Cloud SQL. I tried to see what options are there for streaming from the external PostgreSQL into a Cloud SQL PostgreSQL database, but I could only find information about replicating it in a one time copy, not streaming:
https://cloud.google.com/sql/docs/mysql/replication/replication-from-external
The reason why I want this streaming into BigQuery is that I am using Google Data Studio to create reports from the external PostgreSQL, which works great, but GDS can only accept SQL query parameters if it comes from a Google BigQuery database. E.g. if we have a table with 1M entries, and we want a Google Data Studio parameter to be added by the user, this will turn into a:
SELECT * from table WHERE id=#parameter;
which means that the query will be faster, and won't hit the 100K records limit in Google Data Studio.
What's the best way of creating a connection between an external PostgreSQL (read-only access) and Google BigQuery so that when querying via BigQuery, one gets the same live results as querying the external PostgreSQL?
Perhaps you missed the options stated on the google cloud user guide?
https://cloud.google.com/sql/docs/mysql/replication/replication-from-external#setup-replication
Notice in this section, it says:
"When you set up your replication settings, you can also decide whether the Cloud SQL replica should stay in-sync with the source database server after the initial import is complete. A replica that should stay in-sync is online. A replica that is only updated once, is offline."
I suspect online mode is what you are looking for.
What you are looking for will require some architecture design based on your needs and some coding. There isn't a feature to automatically sync your PostgreSQL database with BigQuery (apart from the EXTERNAL_QUERY() functionality that has some limitations - 1 connection per db - performance - total of connections - etc).
In case you are not looking for the data in real time, what you can do is with Airflow for instance, have a DAG to connect to all your DBs once per day (using KubernetesPodOperator for instance), extract the data (from past day) and loading it into BQ. A typical ETL process, but in this case more EL(T). You can run this process more often if you cannot wait one day for the previous day of data.
On the other hand, if streaming is what you are looking for, then I can think on a Dataflow Job. I guess you can connect using a JDBC connector.
In addition, depending on how you have your pipeline structure, it might be easier to implement (but harder to maintain) if at the same moment you write to your PostgreSQL DB, you also stream your data into BigQuery.
Not sure if you have tried this already, but instead of adding a parameter, if you add a dropdown filter based on a dimension, Data Studio will push that down to the underlying Postgres db in this form:
SELECT * from table WHERE id=$filter_value;
This should achieve the same results you want without going through BigQuery.
We have one Google Cloud SQL instance with 1 vCPU for production. I want to grab a copy of the data by exporting to a bucket. Is this safe to do? As in might it block other operations on the instance?
I think it's important to take into consideration the RDBMS that you are using, it's mentioned in here that PostgreSQL has issues when handling big blobs in an export, and at this other SO post there's an answer with the most votes with hints to have an smoother export, since it can lead to DBs getting unresponsive, which is a pretty well known fact.
In the case of MySQL, the product doc have some tips for this case in this article where it stated:
"If the server is running, it is necessary to perform appropriate locking so that the server does not change database contents during the backup"
And you can achive this by using mysqldump --lock-tables=false into your export command.
We recently migrated a large DB2 database to a new server. It got trimmed a lot in the migration, for instance 10 years of data chopped down to 3, to name a few. But now I find that I need certain data from the old server until after tax season.
How can I run a UNION query in DBeaver that pulls data from two different connections..? What's the proper syntax of the table identifiers in the FROM and JOIN keywords..?
I use DBeaver for my regular SQL work, and I cannot determine how to span a UNION query across two different connections. However, I also use Microsoft Access, and I easily did it there with two Pass-Through queries that are fed to a native Microsoft Access union query.
But how to do it in DBeaver..? I can't understand how to use two connections at the same time.
For instance, here are my connections:
And I need something like this...
SELECT *
FROM ASP7.F_CERTOB.LDHIST
UNION
SELECT *
FROM OLD.VIPDTAB.LDHIST
...but I get the following error, to which I say "No kidding! That's what I want!", lol... =-)
SQL Error [56023]: [SQL0512] Statement references objects in multiple databases.
How can this be done..?
This is not a feature of DBeaver. DBeaver can only access the data that the DB gives it, and this is restricted to a single connection at a time (save for import/export operations). This feature is being considered for development, so keep an eye out for this answer to be outdated sometime in 2019.
You can export data from your OLD database and import it into ASP7 using DBeaver (although vendor tools for this are typically more efficient for this). Then you can do your union as suggested.
Many RDBMS offer a way to logically access foreign databases as if they were local, in which case DBeaver would then be able to access the data from the OLD database (as far as DBeaver is concerned in this situation, all the data is coming from a single connection). In Postgres, for example, one can use a foreign data wrapper to access foreign data.
I'm not familiar with DB2, but a quick Google search suggests that you can set up foreign connections within DB2 using nicknames or three-part-names.
If you check this github issue:
https://github.com/dbeaver/dbeaver/issues/3605
The way to solve this is to create a task and execute it in different connections:
https://github.com/dbeaver/dbeaver/issues/3605#issuecomment-590405154
I'm consistently seeing less than 24 hours uptime on my cloud SQL instance, despite having it set to always on.
It looks like the instance is crashing as I keep losing new users added (and the mysql users table is in myisam so can't recover from a crash as my indoor data tables can).
Is there a problem with Cloud SQL causing this or is it likely to be something with my configuration?
InnoDB is the Google recommended database engine for Cloud SQL.
If MyISAM is a requirement for you, I´d use MySQL on a Google Compute Engine.
Check:
https://cloud.google.com/sql/faq#innodb
and
https://cloud.google.com/sql/docs/launch-checklist
Is it possible to have a MS access backend database (Microsoft JET or Access Database Engine) set up so that whenever entries are inserted/updated those changes are replicated* to a PostgreSQL database?
Two-way synchronization would be nice, but one way would be acceptable.
I know it's popular to link the two and use one as a frontend, but it's essential that both be backend.
Any suggestions?
* ie reflected, synchronized, mirrored
Can you use Microsoft SQL Server Express Edition? Or do you have to use Microsoft Access Database Engine? It's possible you'll have more options using MS SQL express, like more complete triggers and logging.
Either way, you're going to need a way to accumulate a log of changed rows from the source database engine, and a program to sync them to PostgreSQL by reading the log and converting it into suitable PostgreSQL INSERT, UPDATE and DELETE statements.
You could do this by having audit triggers in MADB/Express insert a row into an audit shadow table for every "real" table whenever it changed, including inserting special "row deleted" audit entries. Then your sync program could connect to both MADB/Express, read the audit tables, apply the changes to PostgreSQL, and empty the audit tables.
I'll be surprised if you find anything to do this out of the box. It's one area where Microsoft SQL Server has a big advantage because of all the deep Access and MADB engine integation to support the synchronisation and integration features.
There are some ETL ("Extract, Transform, Load") tools that might be helpful, like Pentaho and Talend. I don't know if you can achieve the desired degree of automation with them though.