def test_basic_resource_numpy_data_type(self):
"""Test basic get bit depth interface
Returns:
None
"""
setup_data = get_image_dict()
resource = BossResourceBasic(setup_data)
assert resource.get_numpy_data_type() == np.uint8
def test_basic_resource_numpy_data_type(self):
"""Test basic get bit depth interface
Returns:
None
"""
setup_data = get_image_dict()
resource = BossResourceBasic(setup_data)
assert resource.get_numpy_data_type() == np.uint8
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)
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, _ = 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")
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)
