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Introduce framework for parallelizing various pg_upgrade tasks.
A number of pg_upgrade steps require connecting to every database in the cluster and running the same query in each one. When there are many databases, these steps are particularly time-consuming, especially since they are performed sequentially, i.e., we connect to a database, run the query, and process the results before moving on to the next database. This commit introduces a new framework that makes it easy to parallelize most of these once-in-each-database tasks by processing multiple databases concurrently. This framework manages a set of slots that follow a simple state machine, and it uses libpq's asynchronous APIs to establish the connections and run the queries. The --jobs option is used to determine the number of slots to use. To use this new task framework, callers simply need to provide the query and a callback function to process its results, and the framework takes care of the rest. A more complete description is provided at the top of the new task.c file. None of the eligible once-in-each-database tasks are converted to use this new framework in this commit. That will be done via several follow-up commits. Reviewed-by: Jeff Davis, Robert Haas, Daniel Gustafsson, Ilya Gladyshev, Corey Huinker Discussion: https://postgr.es/m/20240516211638.GA1688936%40nathanxps13
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@ -118,7 +118,7 @@ PostgreSQL documentation
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<varlistentry>
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<term><option>-j <replaceable class="parameter">njobs</replaceable></option></term>
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<term><option>--jobs=<replaceable class="parameter">njobs</replaceable></option></term>
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<listitem><para>number of simultaneous processes or threads to use
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<listitem><para>number of simultaneous connections and processes/threads to use
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</para></listitem>
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</varlistentry>
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@ -587,8 +587,8 @@ NET STOP postgresql-&majorversion;
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<para>
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The <option>--jobs</option> option allows multiple CPU cores to be used
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for copying/linking of files and to dump and restore database schemas
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in parallel; a good place to start is the maximum of the number of
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for copying/linking of files, dumping and restoring database schemas
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in parallel, etc.; a good place to start is the maximum of the number of
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CPU cores and tablespaces. This option can dramatically reduce the
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time to upgrade a multi-database server running on a multiprocessor
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machine.
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