resource_dict["coord_frame"]["z_start"] = 0 resource_dict["coord_frame"]["z_stop"] = 100000 resource_dict["coord_frame"]["voxel_unit"] = "nanometers" # Setup the resource resource = BossResourceBasic() resource.from_dict(resource_dict) dtype = resource.get_numpy_data_type() # read all tiles from bucket into a slab tile_bucket = TileBucket(proj_info.project_name) data = [] num_z_slices = 0 for tile_key in tile_key_list: try: image_data, message_id, receipt_handle, _ = tile_bucket.getObjectByKey(tile_key) except KeyError: print('Key: {} not found in tile bucket, assuming redelivered SQS message and aborting.'.format( tile_key)) # Remove message so it's not redelivered. ingest_queue.deleteMessage(msg_id, msg_rx_handle) sys.exit("Aborting due to missing tile in bucket") tile_img = np.asarray(Image.open(BytesIO(image_data)), dtype=dtype) data.append(tile_img) num_z_slices += 1 # Make 3D array of image data. It should be in XYZ at this point chunk_data = np.array(data) del data tile_dims = chunk_data.shape
def handler(event, context): # Load settings SETTINGS = BossSettings.load() # Used as a guard against trying to delete the SQS message when lambda is # triggered by SQS. sqs_triggered = 'Records' in event and len(event['Records']) > 0 if sqs_triggered : # Lambda invoked by an SQS trigger. msg_data = json.loads(event['Records'][0]['body']) # Load the project info from the chunk key you are processing chunk_key = msg_data['chunk_key'] proj_info = BossIngestProj.fromSupercuboidKey(chunk_key) proj_info.job_id = msg_data['ingest_job'] else: # Standard async invoke of this lambda. # Load the project info from the chunk key you are processing proj_info = BossIngestProj.fromSupercuboidKey(event["chunk_key"]) proj_info.job_id = event["ingest_job"] # Get message from SQS ingest queue, try for ~2 seconds rx_cnt = 0 msg_data = None msg_id = None msg_rx_handle = None while rx_cnt < 6: ingest_queue = IngestQueue(proj_info) msg = [x for x in ingest_queue.receiveMessage()] if msg: msg = msg[0] print("MESSAGE: {}".format(msg)) print(len(msg)) msg_id = msg[0] msg_rx_handle = msg[1] msg_data = json.loads(msg[2]) print("MESSAGE DATA: {}".format(msg_data)) break else: rx_cnt += 1 print("No message found. Try {} of 6".format(rx_cnt)) time.sleep(1) if not msg_id: # No tiles ready to ingest. print("No ingest message available") return # Get the chunk key of the tiles to ingest. chunk_key = msg_data['chunk_key'] tile_error_queue = TileErrorQueue(proj_info) print("Ingesting Chunk {}".format(chunk_key)) tiles_in_chunk = int(chunk_key.split('&')[1]) # Setup SPDB instance sp = SpatialDB(msg_data['parameters']["KVIO_SETTINGS"], msg_data['parameters']["STATEIO_CONFIG"], msg_data['parameters']["OBJECTIO_CONFIG"]) # Get tile list from Tile Index Table tile_index_db = BossTileIndexDB(proj_info.project_name) # tile_index_result (dict): keys are S3 object keys of the tiles comprising the chunk. tile_index_result = tile_index_db.getCuboid(msg_data["chunk_key"], int(msg_data["ingest_job"])) if tile_index_result is None: # If chunk_key is gone, another lambda uploaded the cuboids and deleted the chunk_key afterwards. if not sqs_triggered: # Remove message so it's not redelivered. ingest_queue.deleteMessage(msg_id, msg_rx_handle) print("Aborting due to chunk key missing from tile index table") return # Sort the tile keys print("Tile Keys: {}".format(tile_index_result["tile_uploaded_map"])) tile_key_list = [x.rsplit("&", 2) for x in tile_index_result["tile_uploaded_map"].keys()] if len(tile_key_list) < tiles_in_chunk: print("Not a full set of 16 tiles. Assuming it has handled already, tiles: {}".format(len(tile_key_list))) if not sqs_triggered: ingest_queue.deleteMessage(msg_id, msg_rx_handle) return tile_key_list = sorted(tile_key_list, key=lambda x: int(x[1])) tile_key_list = ["&".join(x) for x in tile_key_list] print("Sorted Tile Keys: {}".format(tile_key_list)) # Augment Resource JSON data so it will instantiate properly that was pruned due to S3 metadata size limits resource_dict = msg_data['parameters']['resource'] _, exp_name, ch_name = resource_dict["boss_key"].split("&") resource_dict["channel"]["name"] = ch_name resource_dict["channel"]["description"] = "" resource_dict["channel"]["sources"] = [] resource_dict["channel"]["related"] = [] resource_dict["channel"]["default_time_sample"] = 0 resource_dict["channel"]["downsample_status"] = "NOT_DOWNSAMPLED" resource_dict["experiment"]["name"] = exp_name resource_dict["experiment"]["description"] = "" resource_dict["experiment"]["num_time_samples"] = 1 resource_dict["experiment"]["time_step"] = None resource_dict["experiment"]["time_step_unit"] = None resource_dict["coord_frame"]["name"] = "cf" resource_dict["coord_frame"]["name"] = "" resource_dict["coord_frame"]["x_start"] = 0 resource_dict["coord_frame"]["x_stop"] = 100000 resource_dict["coord_frame"]["y_start"] = 0 resource_dict["coord_frame"]["y_stop"] = 100000 resource_dict["coord_frame"]["z_start"] = 0 resource_dict["coord_frame"]["z_stop"] = 100000 resource_dict["coord_frame"]["voxel_unit"] = "nanometers" # Setup the resource resource = BossResourceBasic() resource.from_dict(resource_dict) dtype = resource.get_numpy_data_type() # read all tiles from bucket into a slab tile_bucket = TileBucket(proj_info.project_name) data = [] num_z_slices = 0 for tile_key in tile_key_list: try: image_data, message_id, receipt_handle, metadata = tile_bucket.getObjectByKey(tile_key) except KeyError: print('Key: {} not found in tile bucket, assuming redelivered SQS message and aborting.'.format( tile_key)) if not sqs_triggered: # Remove message so it's not redelivered. ingest_queue.deleteMessage(msg_id, msg_rx_handle) print("Aborting due to missing tile in bucket") return image_bytes = BytesIO(image_data) image_size = image_bytes.getbuffer().nbytes # Get tiles size from metadata, need to shape black tile if actual tile is corrupt. if 'x_size' in metadata: tile_size_x = metadata['x_size'] else: print('MetadataMissing: x_size not in tile metadata: using 1024.') tile_size_x = 1024 if 'y_size' in metadata: tile_size_y = metadata['y_size'] else: print('MetadataMissing: y_size not in tile metadata: using 1024.') tile_size_y = 1024 if image_size == 0: print('TileError: Zero length tile, using black instead: {}'.format(tile_key)) error_msg = 'Zero length tile' enqueue_tile_error(tile_error_queue, tile_key, chunk_key, error_msg) tile_img = np.zeros((tile_size_x, tile_size_y), dtype=dtype) else: try: tile_img = np.asarray(Image.open(image_bytes), dtype=dtype) except TypeError as te: print('TileError: Incomplete tile, using black instead (tile_size_in_bytes, tile_key): {}, {}' .format(image_size, tile_key)) error_msg = 'Incomplete tile' enqueue_tile_error(tile_error_queue, tile_key, chunk_key, error_msg) tile_img = np.zeros((tile_size_x, tile_size_y), dtype=dtype) except OSError as oe: print('TileError: OSError, using black instead (tile_size_in_bytes, tile_key): {}, {} ErrorMessage: {}' .format(image_size, tile_key, oe)) error_msg = 'OSError: {}'.format(oe) enqueue_tile_error(tile_error_queue, tile_key, chunk_key, error_msg) tile_img = np.zeros((tile_size_x, tile_size_y), dtype=dtype) data.append(tile_img) num_z_slices += 1 # Make 3D array of image data. It should be in XYZ at this point chunk_data = np.array(data) del data tile_dims = chunk_data.shape # Break into Cube instances print("Tile Dims: {}".format(tile_dims)) print("Num Z Slices: {}".format(num_z_slices)) num_x_cuboids = int(math.ceil(tile_dims[2] / CUBOIDSIZE[proj_info.resolution][0])) num_y_cuboids = int(math.ceil(tile_dims[1] / CUBOIDSIZE[proj_info.resolution][1])) print("Num X Cuboids: {}".format(num_x_cuboids)) print("Num Y Cuboids: {}".format(num_y_cuboids)) chunk_key_parts = BossUtil.decode_chunk_key(chunk_key) t_index = chunk_key_parts['t_index'] for x_idx in range(0, num_x_cuboids): for y_idx in range(0, num_y_cuboids): # TODO: check time series support cube = Cube.create_cube(resource, CUBOIDSIZE[proj_info.resolution]) cube.zeros() # Compute Morton ID # TODO: verify Morton indices correct! print(chunk_key_parts) morton_x_ind = x_idx + (chunk_key_parts["x_index"] * num_x_cuboids) morton_y_ind = y_idx + (chunk_key_parts["y_index"] * num_y_cuboids) print("Morton X: {}".format(morton_x_ind)) print("Morton Y: {}".format(morton_y_ind)) morton_index = XYZMorton([morton_x_ind, morton_y_ind, int(chunk_key_parts['z_index'])]) # Insert sub-region from chunk_data into cuboid x_start = x_idx * CUBOIDSIZE[proj_info.resolution][0] x_end = x_start + CUBOIDSIZE[proj_info.resolution][0] x_end = min(x_end, tile_dims[2]) y_start = y_idx * CUBOIDSIZE[proj_info.resolution][1] y_end = y_start + CUBOIDSIZE[proj_info.resolution][1] y_end = min(y_end, tile_dims[1]) z_end = CUBOIDSIZE[proj_info.resolution][2] # TODO: get sub-array w/o making a copy. print("Yrange: {}".format(y_end - y_start)) print("Xrange: {}".format(x_end - x_start)) print("X start: {}".format(x_start)) print("X stop: {}".format(x_end)) cube.data[0, 0:num_z_slices, 0:(y_end - y_start), 0:(x_end - x_start)] = chunk_data[0:num_z_slices, y_start:y_end, x_start:x_end] # Create object key object_key = sp.objectio.generate_object_key(resource, proj_info.resolution, t_index, morton_index) print("Object Key: {}".format(object_key)) # Put object in S3 sp.objectio.put_objects([object_key], [cube.to_blosc()]) # Add object to index sp.objectio.add_cuboid_to_index(object_key, ingest_job=int(msg_data["ingest_job"])) # Update id indices if this is an annotation channel # We no longer index during ingest. #if resource.data['channel']['type'] == 'annotation': # try: # sp.objectio.update_id_indices( # resource, proj_info.resolution, [object_key], [cube.data]) # except SpdbError as ex: # sns_client = boto3.client('sns') # topic_arn = msg_data['parameters']["OBJECTIO_CONFIG"]["prod_mailing_list"] # msg = 'During ingest:\n{}\nCollection: {}\nExperiment: {}\n Channel: {}\n'.format( # ex.message, # resource.data['collection']['name'], # resource.data['experiment']['name'], # resource.data['channel']['name']) # sns_client.publish( # TopicArn=topic_arn, # Subject='Object services misuse', # Message=msg) lambda_client = boto3.client('lambda', region_name=SETTINGS.REGION_NAME) names = AWSNames.create_from_lambda_name(context.function_name) delete_tiles_data = { 'tile_key_list': tile_key_list, 'region': SETTINGS.REGION_NAME, 'bucket': tile_bucket.bucket.name } # Delete tiles from tile bucket. lambda_client.invoke( FunctionName=names.delete_tile_objs_lambda, InvocationType='Event', Payload=json.dumps(delete_tiles_data).encode() ) delete_tile_entry_data = { 'tile_index': tile_index_db.table.name, 'region': SETTINGS.REGION_NAME, 'chunk_key': chunk_key, 'task_id': msg_data['ingest_job'] } # Delete entry from tile index. lambda_client.invoke( FunctionName=names.delete_tile_index_entry_lambda, InvocationType='Event', Payload=json.dumps(delete_tile_entry_data).encode() ) if not sqs_triggered: # Delete message since it was processed successfully ingest_queue.deleteMessage(msg_id, msg_rx_handle)
def handler(event, context): # Load settings SETTINGS = BossSettings.load() # Used as a guard against trying to delete the SQS message when lambda is # triggered by SQS. sqs_triggered = 'Records' in event and len(event['Records']) > 0 if sqs_triggered : # Lambda invoked by an SQS trigger. msg_data = json.loads(event['Records'][0]['body']) # Load the project info from the chunk key you are processing chunk_key = msg_data['chunk_key'] proj_info = BossIngestProj.fromSupercuboidKey(chunk_key) proj_info.job_id = msg_data['ingest_job'] else: # Standard async invoke of this lambda. # Load the project info from the chunk key you are processing proj_info = BossIngestProj.fromSupercuboidKey(event["chunk_key"]) proj_info.job_id = event["ingest_job"] # Get message from SQS ingest queue, try for ~2 seconds rx_cnt = 0 msg_data = None msg_id = None msg_rx_handle = None while rx_cnt < 6: ingest_queue = IngestQueue(proj_info) try: msg = [x for x in ingest_queue.receiveMessage()] # StopIteration may be converted to a RunTimeError. except (StopIteration, RuntimeError): msg = None if msg: msg = msg[0] print("MESSAGE: {}".format(msg)) print(len(msg)) msg_id = msg[0] msg_rx_handle = msg[1] msg_data = json.loads(msg[2]) print("MESSAGE DATA: {}".format(msg_data)) break else: rx_cnt += 1 print("No message found. Try {} of 6".format(rx_cnt)) time.sleep(1) if not msg_id: # No tiles ready to ingest. print("No ingest message available") return # Get the chunk key of the tiles to ingest. chunk_key = msg_data['chunk_key'] tile_error_queue = TileErrorQueue(proj_info) print("Ingesting Chunk {}".format(chunk_key)) tiles_in_chunk = int(chunk_key.split('&')[1]) # Setup SPDB instance sp = SpatialDB(msg_data['parameters']["KVIO_SETTINGS"], msg_data['parameters']["STATEIO_CONFIG"], msg_data['parameters']["OBJECTIO_CONFIG"]) # Get tile list from Tile Index Table tile_index_db = BossTileIndexDB(proj_info.project_name) # tile_index_result (dict): keys are S3 object keys of the tiles comprising the chunk. tile_index_result = tile_index_db.getCuboid(msg_data["chunk_key"], int(msg_data["ingest_job"])) if tile_index_result is None: # If chunk_key is gone, another lambda uploaded the cuboids and deleted the chunk_key afterwards. if not sqs_triggered: # Remove message so it's not redelivered. ingest_queue.deleteMessage(msg_id, msg_rx_handle) print("Aborting due to chunk key missing from tile index table") return # Sort the tile keys print("Tile Keys: {}".format(tile_index_result["tile_uploaded_map"])) tile_key_list = [x.rsplit("&", 2) for x in tile_index_result["tile_uploaded_map"].keys()] if len(tile_key_list) < tiles_in_chunk: print("Not a full set of 16 tiles. Assuming it has handled already, tiles: {}".format(len(tile_key_list))) if not sqs_triggered: ingest_queue.deleteMessage(msg_id, msg_rx_handle) return tile_key_list = sorted(tile_key_list, key=lambda x: int(x[1])) tile_key_list = ["&".join(x) for x in tile_key_list] print("Sorted Tile Keys: {}".format(tile_key_list)) # Augment Resource JSON data so it will instantiate properly that was pruned due to S3 metadata size limits resource_dict = msg_data['parameters']['resource'] _, exp_name, ch_name = resource_dict["boss_key"].split("&") resource_dict["channel"]["name"] = ch_name resource_dict["channel"]["description"] = "" resource_dict["channel"]["sources"] = [] resource_dict["channel"]["related"] = [] resource_dict["channel"]["default_time_sample"] = 0 resource_dict["channel"]["downsample_status"] = "NOT_DOWNSAMPLED" resource_dict["experiment"]["name"] = exp_name resource_dict["experiment"]["description"] = "" resource_dict["experiment"]["num_time_samples"] = 1 resource_dict["experiment"]["time_step"] = None resource_dict["experiment"]["time_step_unit"] = None resource_dict["coord_frame"]["name"] = "cf" resource_dict["coord_frame"]["name"] = "" resource_dict["coord_frame"]["x_start"] = 0 resource_dict["coord_frame"]["x_stop"] = 100000 resource_dict["coord_frame"]["y_start"] = 0 resource_dict["coord_frame"]["y_stop"] = 100000 resource_dict["coord_frame"]["z_start"] = 0 resource_dict["coord_frame"]["z_stop"] = 100000 resource_dict["coord_frame"]["voxel_unit"] = "nanometers" # Setup the resource resource = BossResourceBasic() resource.from_dict(resource_dict) dtype = resource.get_numpy_data_type() # read all tiles from bucket into a slab tile_bucket = TileBucket(proj_info.project_name) data = [] num_z_slices = 0 for tile_key in tile_key_list: try: image_data, message_id, receipt_handle, metadata = tile_bucket.getObjectByKey(tile_key) except KeyError: print('Key: {} not found in tile bucket, assuming redelivered SQS message and aborting.'.format( tile_key)) if not sqs_triggered: # Remove message so it's not redelivered. ingest_queue.deleteMessage(msg_id, msg_rx_handle) print("Aborting due to missing tile in bucket") return image_bytes = BytesIO(image_data) image_size = image_bytes.getbuffer().nbytes # Get tiles size from metadata, need to shape black tile if actual tile is corrupt. if 'x_size' in metadata: tile_size_x = metadata['x_size'] else: print('MetadataMissing: x_size not in tile metadata: using 1024.') tile_size_x = 1024 if 'y_size' in metadata: tile_size_y = metadata['y_size'] else: print('MetadataMissing: y_size not in tile metadata: using 1024.') tile_size_y = 1024 if image_size == 0: print('TileError: Zero length tile, using black instead: {}'.format(tile_key)) error_msg = 'Zero length tile' enqueue_tile_error(tile_error_queue, tile_key, chunk_key, error_msg) tile_img = np.zeros((tile_size_x, tile_size_y), dtype=dtype) else: try: # DP NOTE: Issues when specifying dtype in the asarray function with Pillow ver 8.3.1. # Fixed by separating array instantiation and dtype assignment. tile_img = np.asarray(Image.open(image_bytes)) tile_img = tile_img.astype(dtype) except TypeError as te: print('TileError: Incomplete tile, using black instead (tile_size_in_bytes, tile_key): {}, {}' .format(image_size, tile_key)) error_msg = 'Incomplete tile' enqueue_tile_error(tile_error_queue, tile_key, chunk_key, error_msg) tile_img = np.zeros((tile_size_x, tile_size_y), dtype=dtype) except OSError as oe: print('TileError: OSError, using black instead (tile_size_in_bytes, tile_key): {}, {} ErrorMessage: {}' .format(image_size, tile_key, oe)) error_msg = 'OSError: {}'.format(oe) enqueue_tile_error(tile_error_queue, tile_key, chunk_key, error_msg) tile_img = np.zeros((tile_size_x, tile_size_y), dtype=dtype) data.append(tile_img) num_z_slices += 1 # Make 3D array of image data. It should be in XYZ at this point chunk_data = np.array(data) del data tile_dims = chunk_data.shape # Break into Cube instances print("Tile Dims: {}".format(tile_dims)) print("Num Z Slices: {}".format(num_z_slices)) num_x_cuboids = int(math.ceil(tile_dims[2] / CUBOIDSIZE[proj_info.resolution][0])) num_y_cuboids = int(math.ceil(tile_dims[1] / CUBOIDSIZE[proj_info.resolution][1])) print("Num X Cuboids: {}".format(num_x_cuboids)) print("Num Y Cuboids: {}".format(num_y_cuboids)) chunk_key_parts = BossUtil.decode_chunk_key(chunk_key) t_index = chunk_key_parts['t_index'] for x_idx in range(0, num_x_cuboids): for y_idx in range(0, num_y_cuboids): # TODO: check time series support cube = Cube.create_cube(resource, CUBOIDSIZE[proj_info.resolution]) cube.zeros() # Compute Morton ID # TODO: verify Morton indices correct! print(chunk_key_parts) morton_x_ind = x_idx + (chunk_key_parts["x_index"] * num_x_cuboids) morton_y_ind = y_idx + (chunk_key_parts["y_index"] * num_y_cuboids) print("Morton X: {}".format(morton_x_ind)) print("Morton Y: {}".format(morton_y_ind)) morton_index = XYZMorton([morton_x_ind, morton_y_ind, int(chunk_key_parts['z_index'])]) # Insert sub-region from chunk_data into cuboid x_start = x_idx * CUBOIDSIZE[proj_info.resolution][0] x_end = x_start + CUBOIDSIZE[proj_info.resolution][0] x_end = min(x_end, tile_dims[2]) y_start = y_idx * CUBOIDSIZE[proj_info.resolution][1] y_end = y_start + CUBOIDSIZE[proj_info.resolution][1] y_end = min(y_end, tile_dims[1]) z_end = CUBOIDSIZE[proj_info.resolution][2] # TODO: get sub-array w/o making a copy. print("Yrange: {}".format(y_end - y_start)) print("Xrange: {}".format(x_end - x_start)) print("X start: {}".format(x_start)) print("X stop: {}".format(x_end)) cube.data[0, 0:num_z_slices, 0:(y_end - y_start), 0:(x_end - x_start)] = chunk_data[0:num_z_slices, y_start:y_end, x_start:x_end] # Create object key object_key = sp.objectio.generate_object_key(resource, proj_info.resolution, t_index, morton_index) print("Object Key: {}".format(object_key)) # Put object in S3 sp.objectio.put_objects([object_key], [cube.to_blosc()]) # Add object to index sp.objectio.add_cuboid_to_index(object_key, ingest_job=int(msg_data["ingest_job"])) # Update id indices if this is an annotation channel # We no longer index during ingest. #if resource.data['channel']['type'] == 'annotation': # try: # sp.objectio.update_id_indices( # resource, proj_info.resolution, [object_key], [cube.data]) # except SpdbError as ex: # sns_client = boto3.client('sns') # topic_arn = msg_data['parameters']["OBJECTIO_CONFIG"]["prod_mailing_list"] # msg = 'During ingest:\n{}\nCollection: {}\nExperiment: {}\n Channel: {}\n'.format( # ex.message, # resource.data['collection']['name'], # resource.data['experiment']['name'], # resource.data['channel']['name']) # sns_client.publish( # TopicArn=topic_arn, # Subject='Object services misuse', # Message=msg) lambda_client = boto3.client('lambda', region_name=SETTINGS.REGION_NAME) names = AWSNames.from_lambda(context.function_name) delete_tiles_data = { 'tile_key_list': tile_key_list, 'region': SETTINGS.REGION_NAME, 'bucket': tile_bucket.bucket.name } # Delete tiles from tile bucket. lambda_client.invoke( FunctionName=names.delete_tile_objs.lambda_, InvocationType='Event', Payload=json.dumps(delete_tiles_data).encode() ) delete_tile_entry_data = { 'tile_index': tile_index_db.table.name, 'region': SETTINGS.REGION_NAME, 'chunk_key': chunk_key, 'task_id': msg_data['ingest_job'] } # Delete entry from tile index. lambda_client.invoke( FunctionName=names.delete_tile_index_entry.lambda_, InvocationType='Event', Payload=json.dumps(delete_tile_entry_data).encode() ) if not sqs_triggered: # Delete message since it was processed successfully ingest_queue.deleteMessage(msg_id, msg_rx_handle)