## Problem
Currently, even if `LAMBDA_REMOTE_DOCKER=1`, we unzip the zip files in the directory they are in, which is usually /var/lib/localstack, which usually has a bind mount to the host.
On docker desktop, due to the use of grpc-FUSE (on macos), this can be very slow, about 200 times slower than on volumes / directly on the host. With experimental virtio filesystem enabled (also on macos), this can be reduced to about 30 times as slow, but still problematic.
This means a lambda may take a lot of time processing, for each additional layer some more. This especially affects nodejs lambdas with huge node_modules folders.

## Probable solution
At least if `LAMBDA_REMOTE_DOCKER=1`, we should leave the initial zip files on the bind mount (for persistence etc), but the working directories after unzipping should be located on non-bind mounts, to speed up the IO for unzipping.
mapping = {}
    function_name = data["FunctionName"]
    enabled = data.get("Enabled", True)
    batch_size = data.get("BatchSize")
    mapping["UUID"] = str(uuid.uuid4())
    mapping["FunctionArn"] = func_arn(function_name)
    mapping["LastProcessingResult"] = "OK"
    mapping["StateTransitionReason"] = "User action"
    mapping["LastModified"] = format_timestamp_for_event_source_mapping()
    mapping["State"] = "Enabled" if enabled in [True, None] else "Disabled"
    mapping["ParallelizationFactor"] = data.get("ParallelizationFactor") or 1
    mapping["Topics"] = data.get("Topics") or []
    mapping["MaximumRetryAttempts"] = data.get("MaximumRetryAttempts") or -1
    if "SelfManagedEventSource" in data:
        source_arn = data["SourceAccessConfigurations"][0]["URI"]
        mapping["SelfManagedEventSource"] = data["SelfManagedEventSource"]
        mapping["SourceAccessConfigurations"] = data["SourceAccessConfigurations"]
    else:
        source_arn = data["EventSourceArn"]
        mapping["EventSourceArn"] = source_arn
        mapping["StartingPosition"] = data.get("StartingPosition") or "LATEST"
    batch_size = check_batch_size_range(source_arn, batch_size)
    mapping["BatchSize"] = batch_size
    if data.get("DestinationConfig"):
        mapping["DestinationConfig"] = data.get("DestinationConfig")
    return mapping
def format_timestamp(timestamp=None):