postgres_metrics package¶
Submodules¶
postgres_metrics.apps module¶
postgres_metrics.metrics module¶
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class
postgres_metrics.metrics.
AvailableExtensions
[source]¶ Bases:
postgres_metrics.metrics.Metric
PostgreSQL can be extended by installing extensions with the CREATE EXTENSION command. The list of available extensions on each database is shown below.
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label
= 'Available Extensions'¶
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slug
= 'available-extensions'¶
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sql
= '\n SELECT\n name,\n default_version,\n installed_version,\n comment\n FROM\n pg_available_extensions\n ORDER BY\n name\n ;\n '¶
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-
class
postgres_metrics.metrics.
CacheHitsMetric
[source]¶ Bases:
postgres_metrics.metrics.Metric
The typical rule for most applications is that only a fraction of its data is regularly accessed. As with many other things data can tend to follow the 80/20 rule with 20% of your data accounting for 80% of the reads and often times its higher than this. Postgres itself actually tracks access patterns of your data and will on its own keep frequently accessed data in cache. Generally you want your database to have a cache hit rate of about 99%.
(Source: http://www.craigkerstiens.com/2012/10/01/understanding-postgres-performance/)
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label
= 'Cache Hits'¶
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slug
= 'cache-hits'¶
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sql
= "\n WITH cache AS (\n SELECT\n sum(heap_blks_read) heap_read,\n sum(heap_blks_hit) heap_hit,\n sum(heap_blks_hit) + sum(heap_blks_read) heap_sum\n FROM\n pg_statio_user_tables\n ) SELECT\n heap_read,\n heap_hit,\n CASE\n WHEN heap_sum = 0 THEN 'N/A'\n ELSE (heap_hit / heap_sum)::text\n END ratio\n FROM\n cache\n ;\n "¶
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-
class
postgres_metrics.metrics.
IndexUsageMetric
[source]¶ Bases:
postgres_metrics.metrics.Metric
While there is no perfect answer, if you’re not somewhere around 99% on any table over 10,000 rows you may want to consider adding an index. When examining where to add an index you should look at what kind of queries you’re running. Generally you’ll want to add indexes where you’re looking up by some other id or on values that you’re commonly filtering on such as created_at fields.
(Source: http://www.craigkerstiens.com/2012/10/01/understanding-postgres-performance/)
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label
= 'Index Usage'¶
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slug
= 'index-usage'¶
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sql
= '\n SELECT\n relname,\n 100 * idx_scan / (seq_scan + idx_scan) percent_of_times_index_used,\n n_live_tup rows_in_table\n FROM\n pg_stat_user_tables\n WHERE\n seq_scan + idx_scan > 0\n ORDER BY\n percent_of_times_index_used DESC\n ;\n '¶
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postgres_metrics.urls module¶
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postgres_metrics.urls.
re_path
(route, view, kwargs=None, name=None, *, Pattern=<class 'django.urls.resolvers.RegexPattern'>)¶