I might be misinterpreting what "functional derivative" and "functional integral" here particularly mean but if I recall correctly,
Given a functional
$$ \int_{x_0}^{x_1} L(x,y(x), y'(x), y''(x) ... y^{[n]}(x)) $$
The functional derivative
$$ \frac{\delta L}{\delta y} $$
Is defined such that if $$ \frac{\delta L}{\delta y} = 0 $$
For some y, then there exists a local optima to the aforementioned functional by fitting appropriate boundary conditions on that y.
Derivation of the functional derivative itself requires substitution of
$$y = U + e k(x) $$
where U is the optimal solution, e is a variable (that we will manipulate and should be thought of as infinitesmally small) and k(x) is an arbitrary test function such that $k(x_0) = k(x_1) = 0$
then:
$$ \frac{d}{de} [\int_{x_0}^{x_1} L(x,u(x) + ek(x), ... u^{[n]}(x) + ek^{[n]}(x)) ] $$
Yields (after fidgeting with integration by parts)
$$\int_{x_0}^{x_1} [k(x) \sum_{i=0}^{n} {(-1)^{i} \frac{d^{i}}{dx^{i}}[\frac{\partial L}{\partial y^{[i]}} ]}] = 0$$
Which implies
$$\int_{x_0}^{x_1} [\sum_{i=0}^{n} {(-1)^{i} \frac{d^{i}}{dx^{i}}[\frac{\partial L}{\partial y^{[i]}} ]}] = 0$$
Whereas:
$$\sum_{i=0}^{n} {(-1)^{i} \frac{d^{i}}{dx^{i}} \frac{\partial L}{\partial y^{[i]}} } = \frac{\delta L}{\delta y} $$
The inverse of the functional derivative is a problem in partial differential equations.
Consider for example the one variable, single order derivative case: aka inverting the euler lagrange equations of
$$\frac{\partial L}{\partial y} - \frac{d}{dx}[\frac{\partial L}{\partial y'}] = H $$
for some functional H(x,y,y'). We can expand the total derivative with respect to x (Assuming our arguments are only x, y,y' to find:
$$\frac{\partial L}{\partial y} - \frac{\partial^2 L}{\partial x y'} - y'\frac{\partial^2 L}{\partial y y'} - y''\frac{\partial^2 L}{\partial (y')^2} = H$$
These can be quite challenging for general H (i'm not even sure if solutions exist for general H). But if $$\frac{\partial^2 H}{\partial (y'')^2} = 0$$ which WILL ALWAYS BE THE CASE if H = $\frac{\delta L}{\delta y} $ for any well defined $L(x,y,y')$. In this case follow the procedure below:
$$ H = u(x,y,y') + y''w(x,y,y') $$
such that
$$ \frac{\partial u}{\partial y''} = 0 $$
and
$$ \frac{\partial w}{\partial y''} = 0 $$
Then it is trivial to showL
$$L = \int \int [w] \partial y'' \partial y'' + y'a_1(x,y) + a_2(x,y)$$
Now take the truncated euler lagrange equation and substitute $\int \int [w] \partial y'' \partial y'' + y'a_1(x,y) + a_2(x,y)$ for $L$ in:
$$\frac{\partial L}{\partial y} - \frac{\partial^2 L}{\partial x y'} - y'\frac{\partial^2 L}{\partial y y'} = u$$
To ultimately derive an expression for $a_2$ in terms of $a_1$, substituting this back into your original definition we conclude that in general the inverse of the functional derivative for a functional H (ie the functional integral of H(x,y,y')) is:
$$ \int H \delta y = y' a_1(x,y) + \int{[u + \int \int [\frac{\partial w}{\partial y}] \partial (y')^2 + \frac{\partial a_1}{\partial x} - \int [\frac{\partial w}{\partial x} + \frac{\partial w}{\partial y}] \partial y'} \partial y + (1 - y')a_1(x,y) + g(x) - \int \int [w] \partial (y')^2 $$
for arbitrary functions of their arguments: $a_1(x,y)$ and $g(x)$
This is certainly not equal to 0. It is also definitely not simplified either. But I suppose if that was soo important you could manage it.
Additional notes,
This is just the case for functionals over (x,y,y') for higher order functionals ex: (x,y,y,y', y'', y''' ....) the functional integral is significantly more complex.
Good luck!