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25.3. Log File Maintenance

25.3. Log File Maintenance

It is a good idea to save the database server's log output somewhere, rather than just discarding it via /dev/null . The log output is invaluable when diagnosing problems.

Note

The server log can contain sensitive information and needs to be protected, no matter how or where it is stored, or the destination to which it is routed. For example, some DDL statements might contain plaintext passwords or other authentication details. Logged statements at the ERROR level might show the SQL source code for applications and might also contain some parts of data rows. Recording data, events and related information is the intended function of this facility, so this is not a leakage or a bug. Please ensure the server logs are visible only to appropriately authorized people.

Log output tends to be voluminous (especially at higher debug levels) so you won't want to save it indefinitely. You need to rotate the log files so that new log files are started and old ones removed after a reasonable period of time.

If you simply direct the stderr of postgres into a file, you will have log output, but the only way to truncate the log file is to stop and restart the server. This might be acceptable if you are using PostgreSQL in a development environment, but few production servers would find this behavior acceptable.

A better approach is to send the server's stderr output to some type of log rotation program. There is a built-in log rotation facility, which you can use by setting the configuration parameter logging_collector to true in postgresql.conf . The control parameters for this program are described in Section 20.8.1. You can also use this approach to capture the log data in machine readable CSV (comma-separated values) format.

Alternatively, you might prefer to use an external log rotation program if you have one that you are already using with other server software. For example, the rotatelogs tool included in the Apache distribution can be used with PostgreSQL . One way to do this is to pipe the server's stderr output to the desired program. If you start the server with pg_ctl , then stderr is already redirected to stdout , so you just need a pipe command, for example:

pg_ctl start | rotatelogs /var/log/pgsql_log 86400

You can combine these approaches by setting up logrotate to collect log files produced by PostgreSQL built-in logging collector. In this case, the logging collector defines the names and location of the log files, while logrotate periodically archives these files. When initiating log rotation, logrotate must ensure that the application sends further output to the new file. This is commonly done with a postrotate script that sends a SIGHUP signal to the application, which then reopens the log file. In PostgreSQL , you can run pg_ctl with the logrotate option instead. When the server receives this command, the server either switches to a new log file or reopens the existing file, depending on the logging configuration (see Section 20.8.1).

Note

When using static log file names, the server might fail to reopen the log file if the max open file limit is reached or a file table overflow occurs. In this case, log messages are sent to the old log file until a successful log rotation. If logrotate is configured to compress the log file and delete it, the server may lose the messages logged in this time frame. To avoid this issue, you can configure the logging collector to dynamically assign log file names and use a prerotate script to ignore open log files.

Another production-grade approach to managing log output is to send it to syslog and let syslog deal with file rotation. To do this, set the configuration parameter log_destination to syslog (to log to syslog only) in postgresql.conf . Then you can send a SIGHUP signal to the syslog daemon whenever you want to force it to start writing a new log file. If you want to automate log rotation, the logrotate program can be configured to work with log files from syslog .

On many systems, however, syslog is not very reliable, particularly with large log messages; it might truncate or drop messages just when you need them the most. Also, on Linux , syslog will flush each message to disk, yielding poor performance. (You can use a - at the start of the file name in the syslog configuration file to disable syncing.)

Note that all the solutions described above take care of starting new log files at configurable intervals, but they do not handle deletion of old, no-longer-useful log files. You will probably want to set up a batch job to periodically delete old log files. Another possibility is to configure the rotation program so that old log files are overwritten cyclically.

pgBadger is an external project that does sophisticated log file analysis. check_postgres provides Nagios alerts when important messages appear in the log files, as well as detection of many other extraordinary conditions.

12.2. Tables and Indexes

12.2. Tables and Indexes

12.2.1. Searching a Table
12.2.2. Creating Indexes

The examples in the previous section illustrated full text matching using simple constant strings. This section shows how to search table data, optionally using indexes.

12.2.2. Creating Indexes

We can create a GIN index ( Section 12.9) to speed up text searches:

CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector('english', body));

Notice that the 2-argument version of to_tsvector is used. Only text search functions that specify a configuration name can be used in expression indexes (Section 11.7). This is because the index contents must be unaffected by default_text_search_config. If they were affected, the index contents might be inconsistent because different entries could contain tsvector s that were created with different text search configurations, and there would be no way to guess which was which. It would be impossible to dump and restore such an index correctly.

Because the two-argument version of to_tsvector was used in the index above, only a query reference that uses the 2-argument version of to_tsvector with the same configuration name will use that index. That is, WHERE to_tsvector('english', body) @@ 'a & b' can use the index, but WHERE to_tsvector(body) @@ 'a & b' cannot. This ensures that an index will be used only with the same configuration used to create the index entries.

It is possible to set up more complex expression indexes wherein the configuration name is specified by another column, e.g.:

CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector(config_name, body));

where config_name is a column in the pgweb table. This allows mixed configurations in the same index while recording which configuration was used for each index entry. This would be useful, for example, if the document collection contained documents in different languages. Again, queries that are meant to use the index must be phrased to match, e.g., WHERE to_tsvector(config_name, body) @@ 'a & b' .

Indexes can even concatenate columns:

CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector('english', title || ' ' || body));

Another approach is to create a separate tsvector column to hold the output of to_tsvector . To keep this column automatically up to date with its source data, use a stored generated column. This example is a concatenation of title and body , using coalesce to ensure that one field will still be indexed when the other is NULL :

ALTER TABLE pgweb
    ADD COLUMN textsearchable_index_col tsvector
               GENERATED ALWAYS AS (to_tsvector('english', coalesce(title, '') || ' ' || coalesce(body, ''))) STORED;

Then we create a GIN index to speed up the search:

CREATE INDEX textsearch_idx ON pgweb USING GIN (textsearchable_index_col);

Now we are ready to perform a fast full text search:

SELECT title
FROM pgweb
WHERE textsearchable_index_col @@ to_tsquery('create & table')
ORDER BY last_mod_date DESC
LIMIT 10;

One advantage of the separate-column approach over an expression index is that it is not necessary to explicitly specify the text search configuration in queries in order to make use of the index. As shown in the example above, the query can depend on default_text_search_config . Another advantage is that searches will be faster, since it will not be necessary to redo the to_tsvector calls to verify index matches. (This is more important when using a GiST index than a GIN index; see Section 12.9.) The expression-index approach is simpler to set up, however, and it requires less disk space since the tsvector representation is not stored explicitly.

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12.2. Tables and Indexes

12.2. Tables and Indexes

12.2.1. Searching a Table
12.2.2. Creating Indexes

The examples in the previous section illustrated full text matching using simple constant strings. This section shows how to search table data, optionally using indexes.

12.2.2. Creating Indexes

We can create a GIN index ( Section 12.9) to speed up text searches:

CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector('english', body));

Notice that the 2-argument version of to_tsvector is used. Only text search functions that specify a configuration name can be used in expression indexes (Section 11.7). This is because the index contents must be unaffected by default_text_search_config. If they were affected, the index contents might be inconsistent because different entries could contain tsvector s that were created with different text search configurations, and there would be no way to guess which was which. It would be impossible to dump and restore such an index correctly.

Because the two-argument version of to_tsvector was used in the index above, only a query reference that uses the 2-argument version of to_tsvector with the same configuration name will use that index. That is, WHERE to_tsvector('english', body) @@ 'a & b' can use the index, but WHERE to_tsvector(body) @@ 'a & b' cannot. This ensures that an index will be used only with the same configuration used to create the index entries.

It is possible to set up more complex expression indexes wherein the configuration name is specified by another column, e.g.:

CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector(config_name, body));

where config_name is a column in the pgweb table. This allows mixed configurations in the same index while recording which configuration was used for each index entry. This would be useful, for example, if the document collection contained documents in different languages. Again, queries that are meant to use the index must be phrased to match, e.g., WHERE to_tsvector(config_name, body) @@ 'a & b' .

Indexes can even concatenate columns:

CREATE INDEX pgweb_idx ON pgweb USING GIN (to_tsvector('english', title || ' ' || body));

Another approach is to create a separate tsvector column to hold the output of to_tsvector . To keep this column automatically up to date with its source data, use a stored generated column. This example is a concatenation of title and body , using coalesce to ensure that one field will still be indexed when the other is NULL :

ALTER TABLE pgweb
    ADD COLUMN textsearchable_index_col tsvector
               GENERATED ALWAYS AS (to_tsvector('english', coalesce(title, '') || ' ' || coalesce(body, ''))) STORED;

Then we create a GIN index to speed up the search:

CREATE INDEX textsearch_idx ON pgweb USING GIN (textsearchable_index_col);

Now we are ready to perform a fast full text search:

SELECT title
FROM pgweb
WHERE textsearchable_index_col @@ to_tsquery('create & table')
ORDER BY last_mod_date DESC
LIMIT 10;

One advantage of the separate-column approach over an expression index is that it is not necessary to explicitly specify the text search configuration in queries in order to make use of the index. As shown in the example above, the query can depend on default_text_search_config . Another advantage is that searches will be faster, since it will not be necessary to redo the to_tsvector calls to verify index matches. (This is more important when using a GiST index than a GIN index; see Section 12.9.) The expression-index approach is simpler to set up, however, and it requires less disk space since the tsvector representation is not stored explicitly.

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37.46. schemata

37.46. schemata

The view schemata contains all schemas in the current database that the current user has access to (by way of being the owner or having some privilege).

Table 37.44. schemata Columns

Column Type

Description

catalog_name sql_identifier

Name of the database that the schema is contained in (always the current database)

schema_name sql_identifier

Name of the schema

schema_owner sql_identifier

Name of the owner of the schema

default_character_set_catalog sql_identifier

Applies to a feature not available in PostgreSQL

default_character_set_schema sql_identifier

Applies to a feature not available in PostgreSQL

default_character_set_name sql_identifier

Applies to a feature not available in PostgreSQL

sql_path character_data

Applies to a feature not available in PostgreSQL


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37.46. schemata

37.46. schemata

The view schemata contains all schemas in the current database that the current user has access to (by way of being the owner or having some privilege).

Table 37.44. schemata Columns

Column Type

Description

catalog_name sql_identifier

Name of the database that the schema is contained in (always the current database)

schema_name sql_identifier

Name of the schema

schema_owner sql_identifier

Name of the owner of the schema

default_character_set_catalog sql_identifier

Applies to a feature not available in PostgreSQL

default_character_set_schema sql_identifier

Applies to a feature not available in PostgreSQL

default_character_set_name sql_identifier

Applies to a feature not available in PostgreSQL

sql_path character_data

Applies to a feature not available in PostgreSQL


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SPI_gettypeid

SPI_gettypeid

SPI_gettypeid — return the data type OID of the specified column

Synopsis

Oid SPI_gettypeid(TupleDesc rowdesc, int colnumber)

Description

SPI_gettypeid returns the OID of the data type of the specified column.

Arguments

TupleDesc rowdesc

input row description

int colnumber

column number (count starts at 1)

Return Value

The OID of the data type of the specified column or InvalidOid on error. On error, SPI_result is set to SPI_ERROR_NOATTRIBUTE .

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