perf script: Add support for exporting to sqlite3

index 7656ff8..f578114 100644
@@ -340,7 +340,8 @@ if branches:
 		'to_sym_offset	bigint,'
 		'to_ip		bigint,'
 		'branch_type	integer,'
-		'in_tx		boolean)')
+		'in_tx		boolean,'
+		'call_path_id	bigint)')
 else:
 	do_query(query, 'CREATE TABLE samples ('
 		'id		bigint		NOT NULL,'

index e78fdc2..ed9f7f3 100644
@@ -160,7 +160,7 @@ class TreeItem():
 				  '( SELECT short_name FROM dsos WHERE id = ( SELECT dso_id FROM symbols WHERE id = ( SELECT symbol_id FROM call_paths WHERE id = call_path_id ) ) ), '
 				  '( SELECT ip FROM call_paths where id = call_path_id ) '
 				  'FROM calls WHERE parent_call_path_id = ' + str(self.call_path_id) + ' AND comm_id = ' + str(self.comm_id) + ' AND thread_id = ' + str(self.thread_id) +
-				  'ORDER BY call_path_id')
+				  ' ORDER BY call_path_id')
 		if not ret:
 			raise Exception("Query failed: " + query.lastError().text())
 		last_call_path_id = 0

index 4b6cdbf..8e8ae3a 100644
@@ -104,9 +104,9 @@ system, asynchronous, interrupt, transaction abort, trace begin, trace end, and
 in transaction, respectively.
 
 While it is possible to create scripts to analyze the data, an alternative
-approach is available to export the data to a postgresql database.  Refer to
-script export-to-postgresql.py for more details, and to script
-call-graph-from-postgresql.py for an example of using the database.
+approach is available to export the data to a sqlite or postgresql database.
+Refer to script export-to-sqlite.py or export-to-postgresql.py for more details,
+and to script call-graph-from-postgresql.py for an example of using the database.
 
 There is also script intel-pt-events.py which provides an example of how to
 unpack the raw data for power events and PTWRITE.

new file mode 100644
index 0000000..070204f
@@ -0,0 +1,8 @@
+#!/bin/bash
+
+#
+# export perf data to a sqlite3 database. Can cover
+# perf ip samples (excluding the tracepoints). No special
+# record requirements, just record what you want to export.
+#
+perf record $@

new file mode 100644
index 0000000..5ff6033
@@ -0,0 +1,29 @@
+#!/bin/bash
+# description: export perf data to a sqlite3 database
+# args: [database name] [columns] [calls]
+n_args=0
+for i in "$@"
+do
+    if expr match "$i" "-" > /dev/null ; then
+	break
+    fi
+    n_args=$(( $n_args + 1 ))
+done
+if [ "$n_args" -gt 3 ] ; then
+    echo "usage: export-to-sqlite-report [database name] [columns] [calls]"
+    exit
+fi
+if [ "$n_args" -gt 2 ] ; then
+    dbname=$1
+    columns=$2
+    calls=$3
+    shift 3
+elif [ "$n_args" -gt 1 ] ; then
+    dbname=$1
+    columns=$2
+    shift 2
+elif [ "$n_args" -gt 0 ] ; then
+    dbname=$1
+    shift
+fi
+perf script $@ -s "$PERF_EXEC_PATH"/scripts/python/export-to-sqlite.py $dbname $columns $calls

451 lines not on this page · raw message

index 8e8ae3a..ab1b082 100644
@@ -106,7 +106,7 @@ in transaction, respectively.
 While it is possible to create scripts to analyze the data, an alternative
 approach is available to export the data to a sqlite or postgresql database.
 Refer to script export-to-sqlite.py or export-to-postgresql.py for more details,
-and to script call-graph-from-postgresql.py for an example of using the database.
+and to script call-graph-from-sql.py for an example of using the database.
 
 There is also script intel-pt-events.py which provides an example of how to
 unpack the raw data for power events and PTWRITE.

similarity index 96%
rename from tools/perf/scripts/python/call-graph-from-postgresql.py
rename to tools/perf/scripts/python/call-graph-from-sql.py
index ed9f7f3..f18406d 100644
@@ -1,6 +1,6 @@
 #!/usr/bin/python2
-# call-graph-from-postgresql.py: create call-graph from postgresql database
-# Copyright (c) 2014, Intel Corporation.
+# call-graph-from-sql.py: create call-graph from postgresql database
+# Copyright (c) 2014-2017, Intel Corporation.
 #
 # This program is free software; you can redistribute it and/or modify it
 # under the terms and conditions of the GNU General Public License,

@@ -17,12 +17,12 @@
 # Following on from the example in the export-to-postgresql.py script, a
 # call-graph can be displayed for the pt_example database like this:
 #
-#	python tools/perf/scripts/python/call-graph-from-postgresql.py pt_example
+#	python tools/perf/scripts/python/call-graph-from-sql.py pt_example
 #
 # Note this script supports connecting to remote databases by setting hostname,
 # port, username, password, and dbname e.g.
 #
-#	python tools/perf/scripts/python/call-graph-from-postgresql.py "hostname=myhost username=myuser password=mypassword dbname=pt_example"
+#	python tools/perf/scripts/python/call-graph-from-sql.py "hostname=myhost username=myuser password=mypassword dbname=pt_example"
 #
 # The result is a GUI window with a tree representing a context-sensitive
 # call-graph.  Expanding a couple of levels of the tree and adjusting column

@@ -291,7 +291,7 @@ class MainWindow(QMainWindow):
 
 if __name__ == '__main__':
 	if (len(sys.argv) < 2):
-		print >> sys.stderr, "Usage is: call-graph-from-postgresql.py <database name>"
+		print >> sys.stderr, "Usage is: call-graph-from-sql.py <database name>"
 		raise Exception("Too few arguments")
 
 	dbname = sys.argv[1]

index f578114..efcaf6c 100644
@@ -59,7 +59,7 @@ import datetime
 #	pt_example=# \q
 #
 # An example of using the database is provided by the script
-# call-graph-from-postgresql.py.  Refer to that script for details.
+# call-graph-from-sql.py.  Refer to that script for details.
 #
 # Tables:
 #

index f18406d..b494a67 100644
@@ -1,5 +1,5 @@
 #!/usr/bin/python2
-# call-graph-from-sql.py: create call-graph from postgresql database
+# call-graph-from-sql.py: create call-graph from sql database
 # Copyright (c) 2014-2017, Intel Corporation.
 #
 # This program is free software; you can redistribute it and/or modify it

@@ -11,16 +11,17 @@
 # FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for
 # more details.
 
-# To use this script you will need to have exported data using the
-# export-to-postgresql.py script.  Refer to that script for details.
+# To use this script you will need to have exported data using either the
+# export-to-sqlite.py or the export-to-postgresql.py script.  Refer to those
+# scripts for details.
 #
-# Following on from the example in the export-to-postgresql.py script, a
+# Following on from the example in the export scripts, a
 # call-graph can be displayed for the pt_example database like this:
 #
 #	python tools/perf/scripts/python/call-graph-from-sql.py pt_example
 #
-# Note this script supports connecting to remote databases by setting hostname,
-# port, username, password, and dbname e.g.
+# Note that for PostgreSQL, this script supports connecting to remote databases
+# by setting hostname, port, username, password, and dbname e.g.
 #
 #	python tools/perf/scripts/python/call-graph-from-sql.py "hostname=myhost username=myuser password=mypassword dbname=pt_example"
 #

@@ -296,24 +297,35 @@ if __name__ == '__main__':
 
 	dbname = sys.argv[1]
 
-	db = QSqlDatabase.addDatabase('QPSQL')
-
-	opts = dbname.split()
-	for opt in opts:
-		if '=' in opt:
-			opt = opt.split('=')
-			if opt[0] == 'hostname':
-				db.setHostName(opt[1])
-			elif opt[0] == 'port':
-				db.setPort(int(opt[1]))
-			elif opt[0] == 'username':
-				db.setUserName(opt[1])
-			elif opt[0] == 'password':
-				db.setPassword(opt[1])
-			elif opt[0] == 'dbname':
-				dbname = opt[1]
-		else:
-			dbname = opt
+	is_sqlite3 = False
+	try:
+		f = open(dbname)
+		if f.read(15) == "SQLite format 3":
+			is_sqlite3 = True
+		f.close()
+	except:
+		pass
+
+	if is_sqlite3:
+		db = QSqlDatabase.addDatabase('QSQLITE')
+	else:
+		db = QSqlDatabase.addDatabase('QPSQL')
+		opts = dbname.split()
+		for opt in opts:
+			if '=' in opt:
+				opt = opt.split('=')
+				if opt[0] == 'hostname':
+					db.setHostName(opt[1])
+				elif opt[0] == 'port':
+					db.setPort(int(opt[1]))
+				elif opt[0] == 'username':
+					db.setUserName(opt[1])
+				elif opt[0] == 'password':
+					db.setPassword(opt[1])
+				elif opt[0] == 'dbname':
+					dbname = opt[1]
+			else:
+				dbname = opt
 
 	db.setDatabaseName(dbname)
 	if not db.open():