# Copyright (C) 2023 The Android Open Source Project # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Contains tables for relevant for TODO.""" from python.generators.trace_processor_table.public import Column as C from python.generators.trace_processor_table.public import ColumnFlag from python.generators.trace_processor_table.public import CppInt32 from python.generators.trace_processor_table.public import CppInt64 from python.generators.trace_processor_table.public import CppOptional from python.generators.trace_processor_table.public import CppSelfTableId from python.generators.trace_processor_table.public import CppString from python.generators.trace_processor_table.public import Table from python.generators.trace_processor_table.public import TableDoc from python.generators.trace_processor_table.public import CppTableId from python.generators.trace_processor_table.public import CppUint32 from python.generators.trace_processor_table.public import WrappingSqlView from src.trace_processor.tables.track_tables import TRACK_TABLE, COUNTER_TRACK_TABLE PROFILER_SMAPS_TABLE = Table( python_module=__file__, class_name='ProfilerSmapsTable', sql_name='profiler_smaps', columns=[ C('upid', CppUint32()), C('ts', CppInt64()), C('path', CppString()), C('size_kb', CppInt64()), C('private_dirty_kb', CppInt64()), C('swap_kb', CppInt64()), C('file_name', CppString()), C('start_address', CppInt64()), C('module_timestamp', CppInt64()), C('module_debugid', CppString()), C('module_debug_path', CppString()), C('protection_flags', CppInt64()), C('private_clean_resident_kb', CppInt64()), C('shared_dirty_resident_kb', CppInt64()), C('shared_clean_resident_kb', CppInt64()), C('locked_kb', CppInt64()), C('proportional_resident_kb', CppInt64()), ], tabledoc=TableDoc( doc=''' The profiler smaps contains the memory stats for virtual memory ranges captured by the [heap profiler](/docs/data-sources/native-heap-profiler.md). ''', group='Callstack profilers', columns={ 'upid': '''The unique PID of the process.''', 'ts': '''Timestamp of the snapshot. Multiple rows will have the same timestamp.''', 'path': '''The mmaped file, as per /proc/pid/smaps.''', 'size_kb': '''Total size of the mapping.''', 'private_dirty_kb': '''KB of this mapping that are private dirty RSS.''', 'swap_kb': '''KB of this mapping that are in swap.''', 'file_name': '''''', 'start_address': '''''', 'module_timestamp': '''''', 'module_debugid': '''''', 'module_debug_path': '''''', 'protection_flags': '''''', 'private_clean_resident_kb': '''''', 'shared_dirty_resident_kb': '''''', 'shared_clean_resident_kb': '''''', 'locked_kb': '''''', 'proportional_resident_kb': '''''' })) PACKAGE_LIST_TABLE = Table( python_module=__file__, class_name='PackageListTable', sql_name='package_list', columns=[ C('package_name', CppString()), C('uid', CppInt64()), C('debuggable', CppInt32()), C('profileable_from_shell', CppInt32()), C('version_code', CppInt64()), ], tabledoc=TableDoc( doc=''' Metadata about packages installed on the system. This is generated by the packages_list data-source. ''', group='Misc', columns={ 'package_name': '''name of the package, e.g. com.google.android.gm.''', 'uid': '''UID processes of this package run as.''', 'debuggable': '''bool whether this app is debuggable.''', 'profileable_from_shell': '''bool whether this app is profileable.''', 'version_code': '''versionCode from the APK.''' })) STACK_PROFILE_MAPPING_TABLE = Table( python_module=__file__, class_name='StackProfileMappingTable', sql_name='stack_profile_mapping', columns=[ C('build_id', CppString()), C('exact_offset', CppInt64()), C('start_offset', CppInt64()), C('start', CppInt64()), C('end', CppInt64()), C('load_bias', CppInt64()), C('name', CppString()), ], tabledoc=TableDoc( doc=''' A mapping (binary / library) in a process. This is generated by the stack profilers: heapprofd and traced_perf. ''', group='Callstack profilers', columns={ 'build_id': '''Hex-encoded Build ID of the binary / library.''', 'start': '''Start of the mapping in the process' address space.''', 'end': '''End of the mapping in the process' address space.''', 'name': '''Filename of the binary / library.''', 'exact_offset': '''''', 'start_offset': '''''', 'load_bias': '''''' })) STACK_PROFILE_FRAME_TABLE = Table( python_module=__file__, class_name='StackProfileFrameTable', sql_name='stack_profile_frame', columns=[ C('name', CppString()), C('mapping', CppTableId(STACK_PROFILE_MAPPING_TABLE)), C('rel_pc', CppInt64()), C('symbol_set_id', CppOptional(CppUint32()), flags=ColumnFlag.DENSE), C('deobfuscated_name', CppOptional(CppString())), ], tabledoc=TableDoc( doc=''' A frame on the callstack. This is a location in a program. This is generated by the stack profilers: heapprofd and traced_perf. ''', group='Callstack profilers', columns={ 'name': '''Name of the function this location is in.''', 'mapping': '''The mapping (library / binary) this location is in.''', 'rel_pc': '''The program counter relative to the start of the mapping.''', 'symbol_set_id': '''If the profile was offline symbolized, the offline symbol information of this frame.''', 'deobfuscated_name': '''Deobfuscated name of the function this location is in.''' })) STACK_PROFILE_CALLSITE_TABLE = Table( python_module=__file__, class_name='StackProfileCallsiteTable', sql_name='stack_profile_callsite', columns=[ C('depth', CppUint32()), C('parent_id', CppOptional(CppSelfTableId())), C('frame_id', CppTableId(STACK_PROFILE_FRAME_TABLE)), ], tabledoc=TableDoc( doc=''' A callsite. This is a list of frames that were on the stack. This is generated by the stack profilers: heapprofd and traced_perf. ''', group='Callstack profilers', columns={ 'depth': '''Distance from the bottom-most frame of the callstack.''', 'parent_id': '''Parent frame on the callstack. NULL for the bottom-most.''', 'frame_id': '''Frame at this position in the callstack.''' })) CPU_PROFILE_STACK_SAMPLE_TABLE = Table( python_module=__file__, class_name='CpuProfileStackSampleTable', sql_name='cpu_profile_stack_sample', columns=[ C('ts', CppInt64(), flags=ColumnFlag.SORTED), C('callsite_id', CppTableId(STACK_PROFILE_CALLSITE_TABLE)), C('utid', CppUint32()), C('process_priority', CppInt32()), ], tabledoc=TableDoc( doc='Table containing stack samples from CPU profiling.', group='Callstack profilers', columns={ 'ts': '''timestamp of the sample.''', 'callsite_id': '''unwound callstack.''', 'utid': '''thread that was active when the sample was taken.''', 'process_priority': '''''' })) PERF_SESSION_TABLE = Table( python_module=__file__, class_name='PerfSessionTable', sql_name='__intrinsic_perf_session', columns=[ C('cmdline', CppOptional(CppString())), ], wrapping_sql_view=WrappingSqlView('perf_session'), tabledoc=TableDoc( doc='''Perf sessions.''', group='Callstack profilers', columns={ 'cmdline': '''Command line used to collect the data.''', })) PERF_SAMPLE_TABLE = Table( python_module=__file__, class_name='PerfSampleTable', sql_name='perf_sample', columns=[ C('ts', CppInt64(), flags=ColumnFlag.SORTED), C('utid', CppUint32()), C('cpu', CppOptional(CppUint32())), C('cpu_mode', CppString()), C('callsite_id', CppOptional(CppTableId(STACK_PROFILE_CALLSITE_TABLE))), C('unwind_error', CppOptional(CppString())), C('perf_session_id', CppTableId(PERF_SESSION_TABLE)), ], tabledoc=TableDoc( doc='''Samples from the traced_perf profiler.''', group='Callstack profilers', columns={ 'ts': '''Timestamp of the sample.''', 'utid': '''Sampled thread.''', 'cpu': '''Core the sampled thread was running on.''', 'cpu_mode': '''Execution state (userspace/kernelspace) of the sampled thread.''', 'callsite_id': '''If set, unwound callstack of the sampled thread.''', 'unwind_error': '''If set, indicates that the unwinding for this sample encountered an error. Such samples still reference the best-effort result via the callsite_id, with a synthetic error frame at the point where unwinding stopped.''', 'perf_session_id': '''Distinguishes samples from different profiling streams (i.e. multiple data sources).''' })) INSTRUMENTS_SAMPLE_TABLE = Table( python_module=__file__, class_name='InstrumentsSampleTable', sql_name='instruments_sample', columns=[ C('ts', CppInt64(), flags=ColumnFlag.SORTED), C('utid', CppUint32()), C('cpu', CppOptional(CppUint32())), C('callsite_id', CppOptional(CppTableId(STACK_PROFILE_CALLSITE_TABLE))), ], tabledoc=TableDoc( doc=''' Samples from MacOS Instruments. ''', group='Callstack profilers', columns={ 'ts': '''Timestamp of the sample.''', 'utid': '''Sampled thread.''', 'cpu': '''Core the sampled thread was running on.''', 'callsite_id': '''If set, unwound callstack of the sampled thread.''', })) SYMBOL_TABLE = Table( python_module=__file__, class_name='SymbolTable', sql_name='stack_profile_symbol', columns=[ C('symbol_set_id', CppUint32(), flags=ColumnFlag.SORTED | ColumnFlag.SET_ID), C('name', CppString()), C('source_file', CppOptional(CppString())), C('line_number', CppOptional(CppUint32())), ], tabledoc=TableDoc( doc=''' Symbolization data for a frame. Rows with the same symbol_set_id describe one callframe, with the most-inlined symbol having id == symbol_set_id. For instance, if the function foo has an inlined call to the function bar, which has an inlined call to baz, the stack_profile_symbol table would look like this. ``` |id|symbol_set_id|name |source_file|line_number| |--|-------------|-------------|-----------|-----------| |1 | 1 |baz |foo.cc | 36 | |2 | 1 |bar |foo.cc | 30 | |3 | 1 |foo |foo.cc | 60 | ``` ''', group='Callstack profilers', columns={ 'name': '''name of the function.''', 'source_file': '''name of the source file containing the function.''', 'line_number': ''' line number of the frame in the source file. This is the exact line for the corresponding program counter, not the beginning of the function. ''', 'symbol_set_id': '''''' })) HEAP_PROFILE_ALLOCATION_TABLE = Table( python_module=__file__, class_name='HeapProfileAllocationTable', sql_name='heap_profile_allocation', columns=[ # TODO(b/193757386): readd the sorted flag once this bug is fixed. C('ts', CppInt64()), C('upid', CppUint32()), C('heap_name', CppString()), C('callsite_id', CppTableId(STACK_PROFILE_CALLSITE_TABLE)), C('count', CppInt64()), C('size', CppInt64()), ], tabledoc=TableDoc( doc=''' Allocations that happened at a callsite. NOTE: this table is not sorted by timestamp intentionanlly - see b/193757386 for details. This is generated by heapprofd. ''', group='Callstack profilers', columns={ 'ts': '''The timestamp the allocations happened at. heapprofd batches allocations and frees, and all data from a dump will have the same timestamp.''', 'upid': '''The unique PID of the allocating process.''', 'callsite_id': '''The callsite the allocation happened at.''', 'count': '''If positive: number of allocations that happened at this callsite. if negative: number of allocations that happened at this callsite that were freed.''', 'size': '''If positive: size of allocations that happened at this callsite. if negative: size of allocations that happened at this callsite that were freed.''', 'heap_name': '''''' })) EXPERIMENTAL_FLAMEGRAPH_TABLE = Table( python_module=__file__, class_name='ExperimentalFlamegraphTable', sql_name='experimental_flamegraph', columns=[ C('profile_type', CppString(), flags=ColumnFlag.HIDDEN), C('ts_in', CppOptional(CppInt64()), flags=ColumnFlag.SORTED | ColumnFlag.HIDDEN), C('ts_constraint', CppOptional(CppString()), flags=ColumnFlag.HIDDEN), C('upid', CppOptional(CppUint32()), flags=ColumnFlag.HIDDEN), C('upid_group', CppOptional(CppString()), flags=ColumnFlag.HIDDEN), C('focus_str', CppOptional(CppString()), flags=ColumnFlag.HIDDEN), C('ts', CppInt64(), flags=ColumnFlag.SORTED), C('depth', CppUint32()), C('name', CppString()), C('map_name', CppString()), C('count', CppInt64()), C('cumulative_count', CppInt64()), C('size', CppInt64()), C('cumulative_size', CppInt64()), C('alloc_count', CppInt64()), C('cumulative_alloc_count', CppInt64()), C('alloc_size', CppInt64()), C('cumulative_alloc_size', CppInt64()), C('parent_id', CppOptional(CppSelfTableId())), C('source_file', CppOptional(CppString())), C('line_number', CppOptional(CppUint32())), ], tabledoc=TableDoc( doc=''' Table used to render flamegraphs. This gives cumulative sizes of nodes in the flamegraph. WARNING: This is experimental and the API is subject to change. ''', group='Callstack profilers', columns={ 'ts': '''''', 'upid': '''''', 'profile_type': '''''', 'focus_str': '''''', 'depth': '''''', 'name': '''''', 'map_name': '''''', 'count': '''''', 'cumulative_count': '''''', 'size': '''''', 'cumulative_size': '''''', 'alloc_count': '''''', 'cumulative_alloc_count': '''''', 'alloc_size': '''''', 'cumulative_alloc_size': '''''', 'parent_id': '''''', 'source_file': '''''', 'line_number': '''''', 'upid_group': '''''' })) HEAP_GRAPH_CLASS_TABLE = Table( python_module=__file__, class_name='HeapGraphClassTable', sql_name='heap_graph_class', columns=[ C('name', CppString()), C('deobfuscated_name', CppOptional(CppString())), C('location', CppOptional(CppString())), C('superclass_id', CppOptional(CppSelfTableId())), # classloader_id should really be HeapGraphObject::id, but that # would create a loop, which is currently not possible. # TODO(lalitm): resolve this C('classloader_id', CppOptional(CppUint32())), C('kind', CppString()), ], tabledoc=TableDoc( doc='''''', group='ART Heap Graphs', columns={ 'name': '''(potentially obfuscated) name of the class.''', 'deobfuscated_name': '''if class name was obfuscated and deobfuscation map for it provided, the deobfuscated name.''', 'location': '''the APK / Dex / JAR file the class is contained in. ''', 'superclass_id': '''''', 'classloader_id': '''''', 'kind': '''''' })) HEAP_GRAPH_OBJECT_TABLE = Table( python_module=__file__, class_name='HeapGraphObjectTable', sql_name='heap_graph_object', columns=[ C('upid', CppUint32()), C('graph_sample_ts', CppInt64()), C('self_size', CppInt64()), C('native_size', CppInt64()), C('reference_set_id', CppOptional(CppUint32()), flags=ColumnFlag.DENSE), C('reachable', CppInt32()), C('type_id', CppTableId(HEAP_GRAPH_CLASS_TABLE)), C('root_type', CppOptional(CppString())), C('root_distance', CppInt32(), flags=ColumnFlag.HIDDEN), ], tabledoc=TableDoc( doc=''' The objects on the Dalvik heap. All rows with the same (upid, graph_sample_ts) are one dump. ''', group='ART Heap Graphs', columns={ 'upid': '''Unique PID of the target.''', 'graph_sample_ts': '''timestamp this dump was taken at.''', 'self_size': '''size this object uses on the Java Heap.''', 'native_size': '''approximate amount of native memory used by this object, as reported by libcore.util.NativeAllocationRegistry.size.''', 'reference_set_id': '''join key with heap_graph_reference containing all objects referred in this object's fields.''', 'reachable': '''bool whether this object is reachable from a GC root. If false, this object is uncollected garbage.''', 'type_id': '''class this object is an instance of.''', 'root_type': '''if not NULL, this object is a GC root.''', 'root_distance': '''''' })) HEAP_GRAPH_REFERENCE_TABLE = Table( python_module=__file__, class_name='HeapGraphReferenceTable', sql_name='heap_graph_reference', columns=[ C('reference_set_id', CppUint32(), flags=ColumnFlag.SORTED | ColumnFlag.SET_ID), C('owner_id', CppTableId(HEAP_GRAPH_OBJECT_TABLE)), C('owned_id', CppOptional(CppTableId(HEAP_GRAPH_OBJECT_TABLE))), C('field_name', CppString()), C('field_type_name', CppString()), C('deobfuscated_field_name', CppOptional(CppString())), ], tabledoc=TableDoc( doc=''' Many-to-many mapping between heap_graph_object. This associates the object with given reference_set_id with the objects that are referred to by its fields. ''', group='ART Heap Graphs', columns={ 'reference_set_id': '''Join key to heap_graph_object.''', 'owner_id': '''Id of object that has this reference_set_id.''', 'owned_id': '''Id of object that is referred to.''', 'field_name': '''The field that refers to the object. E.g. Foo.name.''', 'field_type_name': '''The static type of the field. E.g. java.lang.String.''', 'deobfuscated_field_name': '''The deobfuscated name, if field_name was obfuscated and a deobfuscation mapping was provided for it.''' })) VULKAN_MEMORY_ALLOCATIONS_TABLE = Table( python_module=__file__, class_name='VulkanMemoryAllocationsTable', sql_name='vulkan_memory_allocations', columns=[ C('arg_set_id', CppOptional(CppUint32())), C('source', CppString()), C('operation', CppString()), C('timestamp', CppInt64()), C('upid', CppOptional(CppUint32())), C('device', CppOptional(CppInt64())), C('device_memory', CppOptional(CppInt64())), C('memory_type', CppOptional(CppUint32())), C('heap', CppOptional(CppUint32())), C('function_name', CppOptional(CppString())), C('object_handle', CppOptional(CppInt64())), C('memory_address', CppOptional(CppInt64())), C('memory_size', CppOptional(CppInt64())), C('scope', CppString()), ], tabledoc=TableDoc( doc='''''', group='Misc', columns={ 'arg_set_id': '''''', 'source': '''''', 'operation': '''''', 'timestamp': '''''', 'upid': '''''', 'device': '''''', 'device_memory': '''''', 'memory_type': '''''', 'heap': '''''', 'function_name': '''''', 'object_handle': '''''', 'memory_address': '''''', 'memory_size': '''''', 'scope': '''''' })) GPU_COUNTER_GROUP_TABLE = Table( python_module=__file__, class_name='GpuCounterGroupTable', sql_name='gpu_counter_group', columns=[ C('group_id', CppInt32()), C('track_id', CppTableId(TRACK_TABLE)), ], tabledoc=TableDoc( doc='''''', group='Misc', columns={ 'group_id': '''''', 'track_id': '''''' })) PERF_COUNTER_TRACK_TABLE = Table( python_module=__file__, class_name='PerfCounterTrackTable', sql_name='perf_counter_track', columns=[ C('perf_session_id', CppTableId(PERF_SESSION_TABLE)), C('cpu', CppUint32()), C('is_timebase', CppUint32()), ], parent=COUNTER_TRACK_TABLE, tabledoc=TableDoc( doc='Sampled counters\' values for samples in the perf_sample table.', group='Counter Tracks', columns={ 'perf_session_id': 'id of a distict profiling stream', 'cpu': 'the core the sample was taken on', 'is_timebase': ''' If true, indicates this counter was the sampling timebase for this perf_session_id ''' })) # Keep this list sorted. ALL_TABLES = [ CPU_PROFILE_STACK_SAMPLE_TABLE, EXPERIMENTAL_FLAMEGRAPH_TABLE, GPU_COUNTER_GROUP_TABLE, HEAP_GRAPH_CLASS_TABLE, HEAP_GRAPH_OBJECT_TABLE, HEAP_GRAPH_REFERENCE_TABLE, INSTRUMENTS_SAMPLE_TABLE, HEAP_PROFILE_ALLOCATION_TABLE, PACKAGE_LIST_TABLE, PERF_SAMPLE_TABLE, PERF_SESSION_TABLE, PROFILER_SMAPS_TABLE, STACK_PROFILE_CALLSITE_TABLE, STACK_PROFILE_FRAME_TABLE, STACK_PROFILE_MAPPING_TABLE, SYMBOL_TABLE, VULKAN_MEMORY_ALLOCATIONS_TABLE, PERF_COUNTER_TRACK_TABLE, ]