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Support for parallel operations

Vlad Khorsun

Tracker ticket: #7447

The Firebird engine can now execute some tasks using multiple threads in parallel.Currently, parallel execution is implemented for the sweep and the index creation tasks.Parallel execution is supported for both automatic and manual sweep.

To handle a task with multiple threads, the engine runs additional worker threads and creates internal worker attachments.By default, parallel execution is not enabled.There are two ways to enable parallelism in a user attachment:

  1. set the number of parallel workers in DPB using new tag isc_dpb_parallel_workers,

  2. set the default number of parallel workers using new setting ParallelWorkers in firebird.conf.

The gfix utility has a new command-line switch, -parallel, that allows to set the number of parallel workers for the sweep task.

For example, the following will run sweep on the given database and asks the engine to use 4 workers:

gfix -sweep -parallel 4 <database>

gfix uses DPB tag isc_dpb_parallel_workers when attaches to <database>, if switch -parallel is present.

A similar option was also added to gbak.

The new firebird.conf setting ParallelWorkers sets the default number of parallel workers that can be used by any user attachment running parallelizable task.The default value is 1 and means no use of additional parallel workers.The value in the DPB has a higher priority than the setting in firebird.conf.

To control the number of additional workers that can be created by the engine, there are two new settings in firebird.conf:

ParallelWorkers

Sets the default number of parallel workers used by a user attachments.Can be overridden by attachment using tag isc_dpb_parallel_workers in DPB.

MaxParallelWorkers

Limits the maximum number of simultaneously used workers for the given database and Firebird process.

Internal worker attachments are created and managed by the engine itself.The engine maintains per-database pools of worker attachments.The number of threads in each pool is limited by the value of the MaxParallelWorkers setting.The pools are created by each Firebird process independently.

In SuperServer architecture worker attachments are implemented as light-weight system attachments, while in Classic and SuperClassic they look like usual user attachments.All worker attachments are embedded into the creating server process.Thus, in Classic architectures there are no additional server processes.Worker attachments are present in monitoring tables.Idle worker attachments are destroyed after 60 seconds of inactivity.Also, in Classic architectures, worker attachments are destroyed immediately after the last user connection detaches from the database.

Examples:

Set in firebird.conf ParallelWorkers = 4, MaxParallelWorkers = 8 and restart Firebird server.

  1. Connect to test database not using isc_dpb_parallel_workers in DPB and execute a CREATE INDEX …​ SQL statement.On commit, the index will be created and the engine will use three additional worker attachments.In total, four attachments in four threads will work on index creation.

  2. Ensure auto-sweep is enabled for test database.When auto-sweep runs on that database, it will also use three additional workers (and run within four threads).

  3. More than one task at a time can be parallelized: make two attachments and execute a CREATE INDEX …​ in each of them (of course indices to be built should be different).Each index will be created using four attachments (one user and three worker) and four threads.

  4. Run gfix -sweep <database> without specifying switch -parallel: sweep will run using four attachments in four threads.

  5. Run gfix -sweep -parallel 2 <database>: sweep will run using two attachments in two threads.This shows that value in DPB tag isc_dpb_parallel_workers overrides value of setting ParallelWorkers.

Inline minor ODS upgrade

Dmitry Yemanov

Tracker ticket: #7397

This feature allows to upgrade the existing database to the newest ODS version without backup/restore, provided that the database belongs to the same major ODS version.

For example, a database created by Firebird 4.0 uses ODS 13.0 and thus can be upgraded to the ODS 13.1 used by Firebird 5.0.

Notes
  • The upgrade must be done manually, using gfix -upgrade command

  • It requires exclusive access to the database, an error is thrown otherwise

  • The system privilege USE_GFIX_UTILITY is required

  • An upgrade is transactional, all changes are reverted if any error happens

  • After the upgrade, Firebird 4.0 can no longer open the database

Usage
gfix -upgrade <database>
Caution

This is a one-way modification, downgrading backward is impossible.So please make a database copy before upgrading, just to have a recovery point if something goes wrong during the process.

docnext count = 5

More cursor-related details in the plan output

Dmitry Yemanov

Tracker ticket: #7441

Detailed plan output now distinguishes between user-specified SELECT statements (reported as select expressions), PSQL declared cursors and sub-queries.Both legacy and detailed plans now also include information about cursor’s position (line/column) inside their PSQL module.

Examples:

Legacy plan
-- line 23, column 2
PLAN (DISTRICT INDEX (DISTRICT_PK))
-- line 28, column 2
PLAN JOIN (CUSTOMER INDEX (CUSTOMER_PK), WAREHOUSE INDEX(WAREHOUSE_PK))
Detailed plan
Select Expression (line 23, column 2)
    -> Singularity Check
        -> Filter
            -> Table "DISTRICT" Access By ID
                -> Bitmap
                    -> Index "DISTRICT_PK" Unique Scan
Select Expression (line 28, column 2)
    -> Singularity Check
        -> Nested Loop Join (inner)
            -> Filter
                -> Table "CUSTOMER" Access By ID
                    -> Bitmap
                        -> Index "CUSTOMER_PK" Unique Scan
            -> Filter
                -> Table "WAREHOUSE" Access By ID
                    -> Bitmap
                        -> Index "WAREHOUSE_PK" Unique Scan

Line/column numbers (as well as PSQL declared cursors) cannot be seen directly in the plan for user-specified SQL queries, except if the query is EXECUTE BLOCK.However, they are accessible in the MON$EXPLAINED_PLAN column in either MON$STATEMENTS or MON$COMPILED_STATEMENTS tables.

Denser compression of records

Dmitry Yemanov

Tracker ticket: #4723

Starting with ODS 13.1, the engine uses an advanced RLE compression method (with variable-length counter) that stores repeating byte sequences more effectively, thus reducing the storage overhead.This improves compression for long VARCHAR fields (especially UTF8 encoded) that are filled only partially.

Compiled statement cache

Adriano dos Santos Fernandes

Tracker ticket: #7144

The engine now maintains a per-attachment cache of compiled SQL statements.By default, caching is enabled, the caching threshold is defined by the MaxStatementCacheSize parameter in firebird.conf.It can be disabled by setting MaxStatementCacheSize to zero.

The cache is maintained automatically;cached statements are invalidated when required (usually when some DDL statement is executed).

SQL and PSQL profiler

Adriano dos Santos Fernandes

Tracker ticket: #7086

The profiler allows users to measure performance cost of SQL and PSQL code.It’s implemented with a system package in the engine passing data to a profiler plugin.

This documentation treats the engine and plugin parts as a single thing, in the way the default profiler (Default_Profiler) is going to be used.

The RDB$PROFILER package can profile execution of PSQL code, collecting statistics of how many times each line was executed along with its minimum, maximum and accumulated execution times (with nanoseconds precision), as well as open and fetch statistics of implicit and explicit SQL cursors.

To collect profile data, a user must first start a profile session with RDB$PROFILER.START_SESSION.This function returns a profile session ID which is later stored in the profiler snapshot tables to be queried and analyzed by the user.A profiler session may be local (same attachment) or remote (another attachment).

Remote profiling just forwards commands to the remote attachment.So, it’s possible that a client profiles multiple attachments simultaneously.It’s also possible that a locally or remotely started profile session have commands issued by another attachment.

Remotely issued commands require that the target attachment is in an idle state, i.e. not executing others requests.When the target attachment is not idle, the call blocks waiting for that state.

If the remote attachment is from a different user, the calling user must have the system privilege PROFILE_ANY_ATTACHMENT.

After a session is started, PSQL and SQL statements statistics are collected in memory.A profile session collects data only of statements executed in the same attachment associated with the session.Data is aggregated and stored per requests (i.e. a statement execution).When querying snapshot tables, the user may do extra aggregation per statement, or use the auxiliary views that do that automatically.

A session may be paused to temporarily disable statistics collecting.It may be resumed later to return statistics collection in the same session.

A new session may be started when a session is already active.In that case, it has the same semantics of finishing the current session with RDB$PROFILER.FINISH_SESSION(FALSE), so snapshots tables are not updated.

To analyze the collected data, the user must flush the data to the snapshot tables, which can be done by finishing or pausing a session (with FLUSH parameter set to TRUE), or calling RDB$PROFILER.FLUSH.Data is flushed using an autonomous transaction (a transaction started and finished for the specific purpose of profiler data update).

Below is a sample profile session and queries for data analysis.

  1. Preparation — create table and routines that will be analyzed

    create table tab (
        id integer not null,
        val integer not null
    );
    
    set term !;
    
    create or alter function mult(p1 integer, p2 integer) returns integer
    as
    begin
        return p1 * p2;
    end!
    
    create or alter procedure ins
    as
        declare n integer = 1;
    begin
        while (n <= 1000)
        do
        begin
            if (mod(n, 2) = 1) then
                insert into tab values (:n, mult(:n, 2));
            n = n + 1;
        end
    end!
    
    set term ;!
  2. Start profiling

    select rdb$profiler.start_session('Profile Session 1') from rdb$database;
    
    set term !;
    
    execute block
    as
    begin
        execute procedure ins;
        delete from tab;
    end!
    
    set term ;!
    
    execute procedure rdb$profiler.finish_session(true);
    
    execute procedure ins;
    
    select rdb$profiler.start_session('Profile Session 2') from rdb$database;
    
    select mod(id, 5),
           sum(val)
      from tab
      where id <= 50
      group by mod(id, 5)
      order by sum(val);
    
    execute procedure rdb$profiler.finish_session(true);
  3. Data analysis

    set transaction read committed;
    
    select * from plg$prof_sessions;
    
    select * from plg$prof_psql_stats_view;
    
    select * from plg$prof_record_source_stats_view;
    
    select preq.*
      from plg$prof_requests preq
      join plg$prof_sessions pses
        on pses.profile_id = preq.profile_id and
           pses.description = 'Profile Session 1';
    
    select pstat.*
      from plg$prof_psql_stats pstat
      join plg$prof_sessions pses
        on pses.profile_id = pstat.profile_id and
           pses.description = 'Profile Session 1'
      order by pstat.profile_id,
               pstat.request_id,
               pstat.line_num,
               pstat.column_num;
    
    select pstat.*
      from plg$prof_record_source_stats pstat
      join plg$prof_sessions pses
        on pses.profile_id = pstat.profile_id and
           pses.description = 'Profile Session 2'
      order by pstat.profile_id,
               pstat.request_id,
               pstat.cursor_id,
               pstat.record_source_id;

Package routines

Function START_SESSION

RDB$PROFILER.START_SESSION starts a new profiler session, makes it the current session (of the given ATTACHMENT_ID) and returns its identifier.

If FLUSH_INTERVAL is different from NULL, auto-flush is set up in the same way as manually calling RDB$PROFILER.SET_FLUSH_INTERVAL.

If PLUGIN_NAME is NULL (the default), it uses the database configuration DefaultProfilerPlugin.

PLUGIN_OPTIONS are plugin specific options and currently should be NULL for the Default_Profiler plugin.

Input parameters
  • DESCRIPTION type VARCHAR(255) CHARACTER SET UTF8 default NULL

  • FLUSH_INTERVAL type INTEGER default NULL

  • ATTACHMENT_ID type BIGINT NOT NULL default CURRENT_CONNECTION

  • PLUGIN_NAME type VARCHAR(255) CHARACTER SET UTF8 default NULL

  • PLUGIN_OPTIONS type VARCHAR(255) CHARACTER SET UTF8 default NULL

Return type

BIGINT NOT NULL

Procedure PAUSE_SESSION

RDB$PROFILER.PAUSE_SESSION pauses the current profiler session (of the given ATTACHMENT_ID), so the next executed statements statistics are not collected.

If FLUSH is TRUE, the snapshot tables are updated with data up to the current moment, otherwise data remains only in memory for later update.

Calling RDB$PROFILER.PAUSE_SESSION(TRUE) has the same semantics as calling RDB$PROFILER.PAUSE_SESSION(FALSE) followed by RDB$PROFILER.FLUSH (using the same ATTACHMENT_ID).

Input parameters
  • FLUSH type BOOLEAN NOT NULL default FALSE

  • ATTACHMENT_ID type BIGINT NOT NULL default CURRENT_CONNECTION

Procedure RESUME_SESSION

RDB$PROFILER.RESUME_SESSION resumes the current profiler session (of the given ATTACHMENT_ID), if it was paused, so the next executed statements statistics are collected again.

Input parameter
  • ATTACHMENT_ID type BIGINT NOT NULL default CURRENT_CONNECTION

Procedure FINISH_SESSION

RDB$PROFILER.FINISH_SESSION finishes the current profiler session (of the given ATTACHMENT_ID).

If FLUSH is TRUE, the snapshot tables are updated with data of the finished session (and old finished sessions not yet present in the snapshot), otherwise data remains only in memory for later update.

Calling RDB$PROFILER.FINISH_SESSION(TRUE) has the same semantics of calling RDB$PROFILER.FINISH_SESSION(FALSE) followed by RDB$PROFILER.FLUSH (using the same ATTACHMENT_ID).

Input parameters
  • FLUSH type BOOLEAN NOT NULL default TRUE

  • ATTACHMENT_ID type BIGINT NOT NULL default CURRENT_CONNECTION

Procedure CANCEL_SESSION

RDB$PROFILER.CANCEL_SESSION cancels the current profiler session (of the given ATTACHMENT_ID).

All session data present in the profiler plugin is discarded and will not be flushed.

Data already flushed is not deleted automatically.

Input parameter
  • ATTACHMENT_ID type BIGINT NOT NULL default CURRENT_CONNECTION

Procedure DISCARD

RDB$PROFILER.DISCARD removes all sessions (of the given ATTACHMENT_ID) from memory, without flushing them.

If there is an active session, it is cancelled.

Input parameter
  • ATTACHMENT_ID type BIGINT NOT NULL default CURRENT_CONNECTION

Procedure FLUSH

RDB$PROFILER.FLUSH updates the snapshot tables with data from the profile sessions (of the given ATTACHMENT_ID) in memory.

After flushing, the data is stored in tables PLG$PROF_SESSIONS, PLG$PROF_STATEMENTS, PLG$PROF_RECORD_SOURCES, PLG$PROF_REQUESTS, PLG$PROF_PSQL_STATS and PLG$PROF_RECORD_SOURCE_STATS and may be read and analyzed by the user.

Data is updated using an autonomous transaction, so if the procedure is called in a snapshot transaction, data will not be directly readable in the same transaction.

Once flush happens, finished sessions are removed from memory.

Input parameter
  • ATTACHMENT_ID type BIGINT NOT NULL default CURRENT_CONNECTION

Procedure SET_FLUSH_INTERVAL

RDB$PROFILER.SET_FLUSH_INTERVAL turns periodic auto-flush on (when FLUSH_INTERVAL is greater than 0) or off (when FLUSH_INTERVAL is equal to 0).

FLUSH_INTERVAL is interpreted as number of seconds.

Input parameters
  • FLUSH_INTERVAL type INTEGER NOT NULL

  • ATTACHMENT_ID type BIGINT NOT NULL default CURRENT_CONNECTION

Snapshot tables

Snapshot tables (as well views and sequence) are automatically created in the first usage of the profiler.They are owned by the database owner, with read/write permissions for PUBLIC.

When a session is deleted, the related data in other profiler snapshot tables are automatically deleted too through foreign keys with DELETE CASCADE option.

Below is the list of tables that stores profile data.

Table PLG$PROF_SESSIONS

PROFILE_ID type BIGINT

Profile session ID

ATTACHMENT_ID type BIGINT

Attachment ID

USER_NAME type CHAR(63) CHARACTER SET UTF8

Username

DESCRIPTION type VARCHAR(255) CHARACTER SET UTF8

Description passed in RDB$PROFILER.START_SESSION

START_TIMESTAMP type TIMESTAMP WITH TIME ZONE

Moment the profile session was started

FINISH_TIMESTAMP type TIMESTAMP WITH TIME ZONE

Moment the profile session was finished (NULL when not finished)

Primary key

PROFILE_ID

Table PLG$PROF_STATEMENTS

PROFILE_ID type BIGINT

Profile session ID

STATEMENT_ID type BIGINT

Statement ID

PARENT_STATEMENT_ID type BIGINT

Parent statement ID — related to sub routines

STATEMENT_TYPE type VARCHAR(20) CHARACTER SET UTF8

BLOCK, FUNCTION, PROCEDURE or TRIGGER

PACKAGE_NAME type CHAR(63) CHARACTER SET UTF8

Package of FUNCTION or PROCEDURE

ROUTINE_NAME type CHAR(63) CHARACTER SET UTF8

Routine name of FUNCTION, PROCEDURE or TRIGGER

SQL_TEXT type BLOB SUB_TYPE TEXT CHARACTER SET UTF8

SQL text for BLOCK

Primary key

PROFILE_ID, STATEMENT_ID

Table PLG$PROF_CURSORS

PROFILE_ID type BIGINT

Profile session ID

STATEMENT_ID type BIGINT

Statement ID

CURSOR_ID type INTEGER

Cursor ID

NAME type CHAR(63) CHARACTER SET UTF8

Name of explicit cursor

LINE_NUM type INTEGER

Line number of the cursor

COLUMN_NUM type INTEGER

Column number of the cursor

Primary key

PROFILE_ID, STATEMENT_ID, CURSOR_ID

Table PLG$PROF_RECORD_SOURCES

PROFILE_ID type BIGINT

Profile session ID

STATEMENT_ID type BIGINT

Statement ID

CURSOR_ID type INTEGER

Cursor ID

RECORD_SOURCE_ID type INTEGER

Record source ID

PARENT_RECORD_SOURCE_ID type INTEGER

Parent record source ID

LEVEL

Indentation level for the record source

ACCESS_PATH type BLOB SUB_TYPE TEXT CHARACTER SET UTF8

Access path for the record source

Primary key

PROFILE_ID, STATEMENT_ID, CURSOR_ID, RECORD_SOURCE_ID

Table PLG$PROF_REQUESTS

PROFILE_ID type BIGINT

Profile session ID

STATEMENT_ID type BIGINT

Statement ID

REQUEST_ID type BIGINT

Request ID

CALLER_STATEMENT_ID type BIGINT

Caller statement ID

CALLER_REQUEST_ID type BIGINT

Caller request ID

START_TIMESTAMP type TIMESTAMP WITH TIME ZONE

Moment this request was first gathered profile data

FINISH_TIMESTAMP type TIMESTAMP WITH TIME ZONE

Moment this request was finished

TOTAL_ELAPSED_TIME type BIGINT

Accumulated elapsed time (in nanoseconds) of the request

Primary key

PROFILE_ID, REQUEST_ID

Table PLG$PROF_PSQL_STATS

PROFILE_ID type BIGINT

Profile session ID

STATEMENT_ID type BIGINT

Statement ID

REQUEST_ID type BIGINT

Request ID

LINE_NUM type INTEGER

Line number of the statement

COLUMN_NUM type INTEGER

Column number of the statement

COUNTER type BIGINT

Number of executed times of the line/column

MIN_ELAPSED_TIME type BIGINT

Minimal elapsed time (in nanoseconds) of a line/column execution

MAX_ELAPSED_TIME type BIGINT

Maximum elapsed time (in nanoseconds) of a line/column execution

TOTAL_ELAPSED_TIME type BIGINT

Accumulated elapsed time (in nanoseconds) of the line/column executions

Primary key

PROFILE_ID, REQUEST_ID, LINE_NUM, COLUMN_NUM

Table PLG$PROF_RECORD_SOURCE_STATS

PROFILE_ID type BIGINT

Profile session ID

STATEMENT_ID type BIGINT

Statement ID

REQUEST_ID type BIGINT

Request ID

CURSOR_ID type INTEGER

Cursor ID

RECORD_SOURCE_ID type `INTEGER

Record source ID

OPEN_COUNTER type BIGINT

Number of open times of the record source

OPEN_MIN_ELAPSED_TIME type BIGINT

Minimal elapsed time (in nanoseconds) of a record source open

OPEN_MAX_ELAPSED_TIME type BIGINT

Maximum elapsed time (in nanoseconds) of a record source open

OPEN_TOTAL_ELAPSED_TIME type BIGINT

Accumulated elapsed time (in nanoseconds) of the record source openings

FETCH_COUNTER type BIGINT

Number of fetch times of the record source

FETCH_MIN_ELAPSED_TIME type BIGINT

Minimal elapsed time (in nanoseconds) of a record source fetch

FETCH_MAX_ELAPSED_TIME type BIGINT

Maximum elapsed time (in nanoseconds) of a record source fetch

FETCH_TOTAL_ELAPSED_TIME type BIGINT

Accumulated elapsed time (in nanoseconds) of the record source fetches

Primary key

PROFILE_ID, REQUEST_ID, CURSOR_ID, RECORD_SOURCE_ID

Auxiliary views

These views help profile data extraction aggregated at statement level.

They should be the preferred way to analyze the collected data.They can also be used together with the tables to get additional data not present on the views.

After hotspots are found, one can drill down in the data at the request level through the tables.

View PLG$PROF_STATEMENT_STATS_VIEW

select req.profile_id,
       req.statement_id,
       sta.statement_type,
       sta.package_name,
       sta.routine_name,
       sta.parent_statement_id,
       sta_parent.statement_type parent_statement_type,
       sta_parent.routine_name parent_routine_name,
       (select sql_text
          from plg$prof_statements
          where profile_id = req.profile_id and
                statement_id = coalesce(sta.parent_statement_id, req.statement_id)
       ) sql_text,
       count(*) counter,
       min(req.total_elapsed_time) min_elapsed_time,
       max(req.total_elapsed_time) max_elapsed_time,
       cast(sum(req.total_elapsed_time) as bigint) total_elapsed_time,
       cast(sum(req.total_elapsed_time) / count(*) as bigint) avg_elapsed_time
  from plg$prof_requests req
  join plg$prof_statements sta
    on sta.profile_id = req.profile_id and
       sta.statement_id = req.statement_id
  left join plg$prof_statements sta_parent
    on sta_parent.profile_id = sta.profile_id and
       sta_parent.statement_id = sta.parent_statement_id
  group by req.profile_id,
           req.statement_id,
           sta.statement_type,
           sta.package_name,
           sta.routine_name,
           sta.parent_statement_id,
           sta_parent.statement_type,
           sta_parent.routine_name
  order by sum(req.total_elapsed_time) desc

View PLG$PROF_PSQL_STATS_VIEW

select pstat.profile_id,
       pstat.statement_id,
       sta.statement_type,
       sta.package_name,
       sta.routine_name,
       sta.parent_statement_id,
       sta_parent.statement_type parent_statement_type,
       sta_parent.routine_name parent_routine_name,
       (select sql_text
          from plg$prof_statements
          where profile_id = pstat.profile_id and
                statement_id = coalesce(sta.parent_statement_id, pstat.statement_id)
       ) sql_text,
       pstat.line_num,
       pstat.column_num,
       cast(sum(pstat.counter) as bigint) counter,
       min(pstat.min_elapsed_time) min_elapsed_time,
       max(pstat.max_elapsed_time) max_elapsed_time,
       cast(sum(pstat.total_elapsed_time) as bigint) total_elapsed_time,
       cast(sum(pstat.total_elapsed_time) / nullif(sum(pstat.counter), 0) as bigint) avg_elapsed_time
  from plg$prof_psql_stats pstat
  join plg$prof_statements sta
    on sta.profile_id = pstat.profile_id and
       sta.statement_id = pstat.statement_id
  left join plg$prof_statements sta_parent
    on sta_parent.profile_id = sta.profile_id and
       sta_parent.statement_id = sta.parent_statement_id
  group by pstat.profile_id,
           pstat.statement_id,
           sta.statement_type,
           sta.package_name,
           sta.routine_name,
           sta.parent_statement_id,
           sta_parent.statement_type,
           sta_parent.routine_name,
           pstat.line_num,
           pstat.column_num
  order by sum(pstat.total_elapsed_time) desc

View PLG$PROF_RECORD_SOURCE_STATS_VIEW

select rstat.profile_id,
       rstat.statement_id,
       sta.statement_type,
       sta.package_name,
       sta.routine_name,
       sta.parent_statement_id,
       sta_parent.statement_type parent_statement_type,
       sta_parent.routine_name parent_routine_name,
       (select sql_text
          from plg$prof_statements
          where profile_id = rstat.profile_id and
                statement_id = coalesce(sta.parent_statement_id, rstat.statement_id)
       ) sql_text,
       rstat.cursor_id,
       cur.name cursor_name,
       cur.line_num cursor_line_num,
       cur.column_num cursor_column_num,
       rstat.record_source_id,
       recsrc.parent_record_source_id,
       recsrc.level,
       recsrc.access_path,
       cast(sum(rstat.open_counter) as bigint) open_counter,
       min(rstat.open_min_elapsed_time) open_min_elapsed_time,
       max(rstat.open_max_elapsed_time) open_max_elapsed_time,
       cast(sum(rstat.open_total_elapsed_time) as bigint) open_total_elapsed_time,
       cast(sum(rstat.open_total_elapsed_time) / nullif(sum(rstat.open_counter), 0) as bigint) open_avg_elapsed_time,
       cast(sum(rstat.fetch_counter) as bigint) fetch_counter,
       min(rstat.fetch_min_elapsed_time) fetch_min_elapsed_time,
       max(rstat.fetch_max_elapsed_time) fetch_max_elapsed_time,
       cast(sum(rstat.fetch_total_elapsed_time) as bigint) fetch_total_elapsed_time,
       cast(sum(rstat.fetch_total_elapsed_time) / nullif(sum(rstat.fetch_counter), 0) as bigint) fetch_avg_elapsed_time,
       cast(coalesce(sum(rstat.open_total_elapsed_time), 0) + coalesce(sum(rstat.fetch_total_elapsed_time), 0) as bigint) open_fetch_total_elapsed_time
  from plg$prof_record_source_stats rstat
  join plg$prof_cursors cur
    on cur.profile_id = rstat.profile_id and
       cur.statement_id = rstat.statement_id and
       cur.cursor_id = rstat.cursor_id
  join plg$prof_record_sources recsrc
    on recsrc.profile_id = rstat.profile_id and
       recsrc.statement_id = rstat.statement_id and
       recsrc.cursor_id = rstat.cursor_id and
       recsrc.record_source_id = rstat.record_source_id
  join plg$prof_statements sta
    on sta.profile_id = rstat.profile_id and
       sta.statement_id = rstat.statement_id
  left join plg$prof_statements sta_parent
    on sta_parent.profile_id = sta.profile_id and
       sta_parent.statement_id = sta.parent_statement_id
  group by rstat.profile_id,
           rstat.statement_id,
           sta.statement_type,
           sta.package_name,
           sta.routine_name,
           sta.parent_statement_id,
           sta_parent.statement_type,
           sta_parent.routine_name,
           rstat.cursor_id,
           cur.name,
           cur.line_num,
           cur.column_num,
           rstat.record_source_id,
           recsrc.parent_record_source_id,
           recsrc.level,
           recsrc.access_path
  order by coalesce(sum(rstat.open_total_elapsed_time), 0) + coalesce(sum(rstat.fetch_total_elapsed_time), 0) desc

RDB$BLOB_UTIL package

Adriano dos Santos Fernandes

Tracker ticket: #281

This package provides procedures and functions to manipulate BLOBs in a way that standard Firebird functions, like BLOB_APPEND and SUBSTRING, cannot do or are very slow.

These routines operate on binary data directly, even for text BLOBs.

Package routines

Function NEW_BLOB

RDB$BLOB_UTIL.NEW_BLOB creates a new BLOB SUB_TYPE BINARY.It returns a BLOB suitable for data appending, similar to BLOB_APPEND.

The advantage over BLOB_APPEND is that it’s possible to set custom SEGMENTED and TEMP_STORAGE options.

BLOB_APPEND always creates BLOBs in temporary storage, which may not always be the best approach if the created BLOB is going to be stored in a permanent table, as this will require a copy operation.

The BLOB returned from this function, even when TEMP_STORAGE = FALSE, may be used with BLOB_APPEND for appending data.

Input parameters
  • SEGMENTED type BOOLEAN NOT NULL

  • TEMP_STORAGE type BOOLEAN NOT NULL

Return type

BLOB SUB_TYPE BINARY NOT NULL

Function OPEN_BLOB

RDB$BLOB_UTIL.OPEN_BLOB opens an existing BLOB for reading.It returns a handle (an integer bound to the transaction) suitable for use with other functions of this package, like SEEK, READ_DATA and CLOSE_HANDLE.

Handles which are not explicitly closed are closed automatically when the transaction ends.

Input parameter
  • BLOB type BLOB NOT NULL

Return type

INTEGER NOT NULL

Function IS_WRITABLE

RDB$BLOB_UTIL.IS_WRITABLE returns TRUE when a BLOB is suitable for data appending using BLOB_APPEND without copying.

Input parameter
  • BLOB type BLOB NOT NULL

Return type:

BOOLEAN NOT NULL

Function READ_DATA

RDB$BLOB_UTIL.READ_DATA reads chunks of data of a BLOB handle opened with RDB$BLOB_UTIL.OPEN_BLOB.When the BLOB is fully read and there is no more data, it returns NULL.

If LENGTH is passed with a positive number, it returns a VARBINARY with its maximum length.

If LENGTH is NULL it returns just a segment of the BLOB with a maximum length of 32765.

Input parameters
  • HANDLE type INTEGER NOT NULL

  • LENGTH type INTEGER

Return type

VARBINARY(32765)

Function SEEK

RDB$BLOB_UTIL.SEEK sets the position for the next READ_DATA, it returns the new position.

MODE may be 0 (from the start), 1 (from current position) or 2 (from end).

When MODE is 2, OFFSET should be zero or negative.

Input parameters
  • HANDLE type INTEGER NOT NULL

  • MODE type INTEGER NOT NULL

  • OFFSET type INTEGER NOT NULL

Return type

INTEGER NOT NULL

Note

SEEK only works on stream blobs.Attempting to seek on a segmented blob results in error “invalid BLOB type for operation”.

Procedure CANCEL_BLOB

RDB$BLOB_UTIL.CANCEL_BLOB immediately releases a temporary BLOB, like one created with BLOB_APPEND.

If the same BLOB is used after cancel, an “invalid blob id” error will be raised.

Input parameter
  • BLOB type BLOB

Procedure CLOSE_HANDLE

RDB$BLOB_UTIL.CLOSE_HANDLE closes a BLOB handle opened with RDB$BLOB_UTIL.OPEN_BLOB.

Handles which are not explicitly closed are closed automatically when the transaction ends.

Input parameter
  • HANDLE type INTEGER NOT NULL

Examples

Create a BLOB in temporary space and return it in EXECUTE BLOCK
execute block returns (b blob)
as
begin
    -- Create a BLOB handle in the temporary space.
    b = rdb$blob_util.new_blob(false, true);

    -- Add chunks of data.
    b = blob_append(b, '12345');
    b = blob_append(b, '67');

    suspend;
end
Open a BLOB and return chunks of it with EXECUTE BLOCK
execute block returns (s varchar(10))
as
    declare b blob = '1234567';
    declare bhandle integer;
begin
    -- Open the BLOB and get a BLOB handle.
    bhandle = rdb$blob_util.open_blob(b);

    -- Get chunks of data as string and return.

    s = rdb$blob_util.read_data(bhandle, 3);
    suspend;

    s = rdb$blob_util.read_data(bhandle, 3);
    suspend;

    s = rdb$blob_util.read_data(bhandle, 3);
    suspend;

    -- Here EOF is found, so it returns NULL.
    s = rdb$blob_util.read_data(bhandle, 3);
    suspend;

    -- Close the BLOB handle.
    execute procedure rdb$blob_util.close_handle(bhandle);
end
Seek in a blob
set term !;

execute block returns (s varchar(10))
as
    declare b blob;
    declare bhandle integer;
begin
    -- Create a stream BLOB handle.
    b = rdb$blob_util.new_blob(false, true);

    -- Add data.
    b = blob_append(b, '0123456789');

    -- Open the BLOB.
    bhandle = rdb$blob_util.open_blob(b);

    -- Seek to 5 since the start.
    rdb$blob_util.seek(bhandle, 0, 5);
    s = rdb$blob_util.read_data(bhandle, 3);
    suspend;

    -- Seek to 2 since the start.
    rdb$blob_util.seek(bhandle, 0, 2);
    s = rdb$blob_util.read_data(bhandle, 3);
    suspend;

    -- Advance 2.
    rdb$blob_util.seek(bhandle, 1, 2);
    s = rdb$blob_util.read_data(bhandle, 3);
    suspend;

    -- Seek to -1 since the end.
    rdb$blob_util.seek(bhandle, 2, -1);
    s = rdb$blob_util.read_data(bhandle, 3);
    suspend;
end!

set term ;!
Check if blobs are writable
create table t(b blob);

set term !;

execute block returns (bool boolean)
as
    declare b blob;
begin
    b = blob_append(null, 'writable');
    bool = rdb$blob_util.is_writable(b);
    suspend;

    insert into t (b) values ('not writable') returning b into b;
    bool = rdb$blob_util.is_writable(b);
    suspend;
end!

set term ;!